237 AI Engineer jobs in Coimbatore

Overview:

We are looking for an AI Engineer (AI Engineer – Conversational AI & Application Development).

The candidate will need to be collaborative, organised, think out-of-the-box, and be ready to pursue new opportunities. Most importantly, this role is for an individual who is passionate about making a difference through healthcare.

Role Summary

We are seeking a talented AI Engineer to design, develop, and deploy sophisticated conversational agents and AI‑powered applications. Successful candidate will combine strong software‑engineering skills with a deep interest in modern AI techniques. This role will give you the opportunity to work with the latest multi‑agent orchestration frameworks—LangGraph, AutoGen, CrewAI, and Google’s Agent Developer Kit (ADK) —while harnessing the scalability of Google Cloud Platform (GCP) services such as BigQuery, Cloud Run, Kubernetes (GKE), and IAM .

Key Responsibilities

- Design and build multi‑agent conversational systems leveraging LangGraph, AutoGen, CrewAI, ADK, or similar frameworks.

- Collaborate with product managers, designers, and engineers to define user journeys, agent capabilities, and integration points.

- Develop robust, scalable backend services and APIs (Python/Golang/Node.js/Java) to power AI agents and orchestration workflows.

- Apply advanced Natural Language Processing (NLP), Retrieval‑Augmented Generation (RAG), and LLM fine‑tuning techniques for intent recognition, entity extraction, and dynamic dialogue management.

- Deploy and operate conversational workloads on GCP Cloud Run (serverless) and Kubernetes (GKE) , following DevOps best practices and implementing secure access controls with IAM .

- Leverage BigQuery for large‑scale data analytics to train, evaluate, and refine ML models and conversational metrics.

- Design and develop interactive dashboards in Power BI or Tableau to visualize conversational KPIs, model performance, and business insights.

- Integrate conversational agents with enterprise systems (databases, CRMs, ERPs) and third‑party APIs.

- Implement observability, evaluation, and monitoring for agent performance (latency, accuracy, hallucination rate) using tools like Arize Phoenix, Langfuse, and LangSmith .

- Contribute to the full software development lifecycle: requirements, architecture, coding, testing, CI/CD, deployment, and maintenance.

- Troubleshoot and resolve production issues to ensure high availability and optimal performance.

- Document technical designs, decisions, and model specifications for cross‑functional reference.

Required Qualifications

- Bachelor’s or Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related field.

- Proficiency in one or more backend languages/frameworks:

- Python (FastAPI, Flask, Django)

- Java (Spring Boot)

- Node.js (Express, NestJS)

- Go (Gin, Fiber)

- Experience building RESTful or GraphQL APIs and designing microservices.

- Solid grasp of machine‑learning fundamentals: supervised/unsupervised learning, evaluation metrics, feature engineering.

- Familiarity with modern NLP libraries (spaCy, Haystack, Hugging Face Transformers, LlamaIndex).

- Strong version‑control habits (Git, trunk‑based development) and CI/CD pipelines.

- Excellent problem‑solving, communication, and collaboration skills.

- Passion for continuous learning and adapting to emerging AI technologies.

Preferred Qualifications

- Hands‑on experience creating and deploying production‑grade AI chat agents or virtual assistants .

- Working knowledge of LangGraph, AutoGen, CrewAI, ADK , or comparable agent‑orchestration / workflow frameworks.

- Experience with Large Language Models (Gemini, GPT‑4, Claude, Mistral, etc.) and vector databases (Weaviate, Chroma, Pinecone).

- Deep experience with Google Cloud Platform (GCP):

- BigQuery for analytical workloads and feature stores.

- Cloud Run (serverless) for scalable, cost‑efficient microservices.

- Google Kubernetes Engine (GKE) for container orchestration and workload portability.

- Identity and Access Management (IAM) for secure, least‑privilege access control.

- Business‑intelligence expertise in building dashboards and reports with Power BI or Tableau .

- Familiarity with other cloud providers (AWS, Azure) and their AI/ML services.

- Understanding of MLOps (model registry, continuous training, drift monitoring) and LLM observability tools such as Arize Phoenix, Langfuse, and LangSmith .

- Database skills in both SQL (PostgreSQL, BigQuery) and NoSQL (Firestore, DynamoDB).

- Contributions to open‑source AI/ML projects or technical blogging/presentations.

Overview:

We are looking for an AI Engineer (AI Engineer – Conversational AI & Application Development).

The candidate will need to be collaborative, organised, think out-of-the-box, and be ready to pursue new opportunities. Most importantly, this role is for an individual who is passionate about making a difference through healthcare.

Role Summary

We are seeking a talented AI Engineer to design, develop, and deploy sophisticated conversational agents and AI‑powered applications. Successful candidate will combine strong software‑engineering skills with a deep interest in modern AI techniques. This role will give you the opportunity to work with the latest multi‑agent orchestration frameworks—LangGraph, AutoGen, CrewAI, and Google’s Agent Developer Kit (ADK) —while harnessing the scalability of Google Cloud Platform (GCP) services such as BigQuery, Cloud Run, Kubernetes (GKE), and IAM .

Key Responsibilities

- Design and build multi‑agent conversational systems leveraging LangGraph, AutoGen, CrewAI, ADK, or similar frameworks.

- Collaborate with product managers, designers, and engineers to define user journeys, agent capabilities, and integration points.

- Develop robust, scalable backend services and APIs (Python/Golang/Node.js/Java) to power AI agents and orchestration workflows.

- Apply advanced Natural Language Processing (NLP), Retrieval‑Augmented Generation (RAG), and LLM fine‑tuning techniques for intent recognition, entity extraction, and dynamic dialogue management.

- Deploy and operate conversational workloads on GCP Cloud Run (serverless) and Kubernetes (GKE) , following DevOps best practices and implementing secure access controls with IAM .

- Leverage BigQuery for large‑scale data analytics to train, evaluate, and refine ML models and conversational metrics.

- Design and develop interactive dashboards in Power BI or Tableau to visualize conversational KPIs, model performance, and business insights.

- Integrate conversational agents with enterprise systems (databases, CRMs, ERPs) and third‑party APIs.

- Implement observability, evaluation, and monitoring for agent performance (latency, accuracy, hallucination rate) using tools like Arize Phoenix, Langfuse, and LangSmith .

- Contribute to the full software development lifecycle: requirements, architecture, coding, testing, CI/CD, deployment, and maintenance.

- Troubleshoot and resolve production issues to ensure high availability and optimal performance.

- Document technical designs, decisions, and model specifications for cross‑functional reference.

Required Qualifications

- Bachelor’s or Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related field.

- Proficiency in one or more backend languages/frameworks:

- Python (FastAPI, Flask, Django)

- Java (Spring Boot)

- Node.js (Express, NestJS)

- Go (Gin, Fiber)

- Experience building RESTful or GraphQL APIs and designing microservices.

- Solid grasp of machine‑learning fundamentals: supervised/unsupervised learning, evaluation metrics, feature engineering.

- Familiarity with modern NLP libraries (spaCy, Haystack, Hugging Face Transformers, LlamaIndex).

- Strong version‑control habits (Git, trunk‑based development) and CI/CD pipelines.

- Excellent problem‑solving, communication, and collaboration skills.

- Passion for continuous learning and adapting to emerging AI technologies.

Preferred Qualifications

- Hands‑on experience creating and deploying production‑grade AI chat agents or virtual assistants .

- Working knowledge of LangGraph, AutoGen, CrewAI, ADK , or comparable agent‑orchestration / workflow frameworks.

- Experience with Large Language Models (Gemini, GPT‑4, Claude, Mistral, etc.) and vector databases (Weaviate, Chroma, Pinecone).

- Deep experience with Google Cloud Platform (GCP):

- BigQuery for analytical workloads and feature stores.

- Cloud Run (serverless) for scalable, cost‑efficient microservices.

- Google Kubernetes Engine (GKE) for container orchestration and workload portability.

- Identity and Access Management (IAM) for secure, least‑privilege access control.

- Business‑intelligence expertise in building dashboards and reports with Power BI or Tableau .

- Familiarity with other cloud providers (AWS, Azure) and their AI/ML services.

- Understanding of MLOps (model registry, continuous training, drift monitoring) and LLM observability tools such as Arize Phoenix, Langfuse, and LangSmith .

- Database skills in both SQL (PostgreSQL, BigQuery) and NoSQL (Firestore, DynamoDB).

- Contributions to open‑source AI/ML projects or technical blogging/presentations.

Role

• LLM Workflow Builder – design and wire up prompts, tools, memory and agents with LangChain / LangGraph / LangServe.
• API & Micro-Service Owner – ship FastAPI endpoints (REST + streaming) that are secure, observable and lightning fast.
• End-to-End Engineer – own the full lifecycle: code → container → CI/CD → K8s → monitoring, with a bias for rapid, iterative releases.
• Cross-Functional Partner – collaborate with product and design to scope MVPs, estimate effort, and keep delivery on track.

Responsibilities

• Architect, implement and maintain multi-agent workflows and retrieval-augmented pipelines.
• Write clean, typed, tested Python (async, pytest, poetry).
• Instrument and evaluate everything with LangSmith / LangFuse; build guardrails and regression suites for prompts.
• Containerize (Docker) and deploy (Kubernetes, GitHub Actions) with automated rollbacks and alerts.
• Optimize latency, throughput and cost; troubleshoot production issues end-to-end.
• Mentor teammates on best practices in LLM app engineering and DevOps.

Must-Have Skills

• Strong Python craftsmanship and async I/O expertise.
• Proven experience with LangChain or LangGraph in real projects.
• FastAPI (or similar) for building REST / streaming APIs.
• Solid DevOps: Docker, basic Kubernetes, CI/CD pipelines, observability tooling.
• Git proficiency: PR hygiene, code reviews, and clear documentation.

Nice-to-Haves

• Lightweight fine-tuning (LoRA/QLoRA) or embedding-model selection.
• Vector databases (Postgres/pgvector, Milvus, LanceDB).
• Serverless / edge deploys (Fly.io, Cloudflare Workers, AWS Lambda).
• Experience with multi-agent planning frameworks or autonomous tool-use research.

About Fincore

• At Fincore we’re on a mission to to build next-generation AI-native finance technology for enterprises
• Our core values - ownership, customer obsession, truth-seeking, and velocity - guide everything we do
• We are venture-backed and closely collaborate with seasoned technology, finance and AI leaders
• We maintain a small, talent-dense team of domain experts and technologists

What We're Looking For

We are seeking an extremely talented, senior- to staff-level AI engineer to help us pioneer the future of finance and accounting. You must have experience building high-quality, complex, yet maintainable LLM apps and agents, and you should be able to do so in a fraction of the time that most competent people think is possible (in part because of your ability to wield the latest in code generation and intuition for prompt engineering). You must have a strong ability to collaborate with customers directly to build solutions tailored to their business needs.

Must-Have Skills

• 5+ years of experience building backend services in Python, Node.js, or similar
• Deep experience and intuition with LLMs
• Cutting-edge knowledge of code generation and prompting techniques
• Experience building agents and tooling for agents
• Expertise in API design (REST, GraphQL) and relational databases
• Strong problem-solving, communication, and collaboration skills

Good to have

• Top-tier institutes preferred (IIT's, NIT's etc.)
• Experience building fintech software
• Experience working in a large enterprise / big tech

Our Tech Stack: NextJS | Python | LangGraph | AWS | Neo4j | PostgreSQL | MongoDB

About Flam :

We are a fast-growing startup on a mission to revolutionize the MR (Mixed Reality) space through innovative AI. Our projects range from immersive mixed-reality applications to advanced generative AI solutions (e.g., GANs, diffusion models, transformers, large language models, and more). We value creativity, problem-solving, and out-of-the-box thinking above all else—your formal qualifications matter less to us than your ability to push the boundaries of AI technology.

Why MR?

Mixed Reality (MR): Merges the best of both Augmented Reality and Virtual Reality, integrating physical and virtual environments for real-time interaction. We leverage these technologies to create next-generation user experiences that transform how people interact with digital content. Our AI-driven approach ensures these immersive environments are intelligent, adaptive, and personalized.

Role Overview :

We are rapidly expanding our AI team and are hiring across multiple experience levels—from fresh graduates and self-taught enthusiasts to seasoned AI experts. As an AI Engineer/Researcher/Scientist, you will work on cutting-edge AI projects that blend creative design principles with emerging technologies like GANs, diffusion models, transformers, large language models, and MR applications.

You’ll be given the freedom to experiment, innovate, and propose unconventional solutions. We’re looking for fast learners who can dig into research papers and GitHub repositories to test and refine multiple solutions rapidly—ultimately selecting and implementing the best one. If you thrive on minimal instruction, adapt quickly, and love solving complex problems, this role is for you.

Key Responsibilities :

• Investigate, prototype, and implement state-of-the-art AI methods across a wide range of applications—generative models (GANs, diffusion models), transformers, large language models, reinforcement learning, and more.
• Explore and adapt novel approaches to AI-driven interactions and experiences in mixed reality environments.
• Build, train, and optimize deep learning models for various tasks, including computer vision, natural language processing, 3D content generation, and more.
• Quickly learn and implement cutting-edge techniques from research papers, GitHub repositories, and community-driven projects.
• Work closely with designers, product managers, and AR/VR/MR developers to integrate AI solutions seamlessly into mixed-reality applications.
• Participate in brainstorming sessions that bridge AI, design principles, and user experience.
• Stay updated on the latest AI research and emerging technologies, especially in generative AI, transformers, and spatial computing.
• Propose and lead experimental projects that push the boundaries of what is possible with AI in extended reality experiences.
• Identify project challenges independently and develop creative, robust solutions with minimal supervision.
• Continually evaluate technical trade-offs and refine solutions to meet product and design requirements.

Qualifications :

• Passion for AI and a drive to explore cutting-edge research.
• Ability to rapidly learn new tools, frameworks, and concepts, often self-taught or independently researched.
• Creative and unconventional approaches to complex challenges.
• Proficiency in at least one programming language commonly used in AI (e.g., Python) and familiarity with AI frameworks (e.g., TensorFlow, PyTorch).
• Exposure to a variety of AI techniques, including but not limited to generative models, large language models, computer vision, reinforcement learning, or other specialized domains.
• Understanding of Design Principles: How they can be applied to AI solutions, ensuring that user experience remains front and center.
• Experience with AR/VR/MR (Unity, Unreal Engine, OpenCV, etc.) is a bonus, but not mandatory.
• Self-motivated with excellent communication skills and a collaborative mindset.

iCliniq is a pioneering global healthcare technology company committed to democratizing

access to world class medical care. Our mission is to leverage cutting edge technology to

ensure everyone, regardless of location, has access to top tier healthcare services. By

integrating innovative AI solutions and telemedicine, we bridge the gap between patients and

healthcare professionals, providing seamless and efficient medical care worldwide.

We are currently seeking talented and passionate engineers to join our dynamic team with a

culture of collaboration and continuous learning. If you are driven by innovation and eager to

make a significant impact in the healthcare industry, we would love to hear from you. Please

send your resume to . We look forward to connecting with you.

Role: Senior AI Engineer

Experience: 4-7 years

Work location: Onsite

iCliniq’s AI Engineer core responsibilities:

1. Conceptualizing and Designing AI Solutions:

● Identifying AI Opportunities: You will work closely with business stakeholders to

understand their challenges and identify areas where AI can provide significant

advantages. This involves analyzing data, processes and workflows to pinpoint

opportunities for automation, optimization and prediction.

● Solution Architecting: Once an opportunity is identified, you will design the

technical architecture of the AI solution. This involves selecting appropriate

machine learning models, outlining data pipelines and defining the integration

points with existing systems.

2. Building and Training AI Models:

● Data Acquisition and Engineering: You will collaborate with data engineers to

acquire, clean and prepare datasets for training machine learning models. This

may involve data wrangling, feature engineering and ensuring data security and

privacy.

● Model Development and Training: You will develop and train models on the

prepared data. This involves choosing the right algorithms, hyperparameter

tuning and iteratively improving the model's performance through rigorous testing

and evaluation.

3. Deployment and Management:

● Model Integration and Deployment: You will ensure smooth integration, handle

infrastructure considerations and monitor the performance of deployed models.

● Performance Monitoring and Optimization: You will also continuously monitor the

performance of AI models, identify potential biases or drifts and perform

necessary optimizations to maintain accuracy and efficiency over time.

4. Collaboration and Communication:

● Cross Functional Collaboration: You will collaborate with data scientists, software

engineers and product managers throughout the development lifecycle. Effective

communication and knowledge sharing are essential for a successful outcome.

● Stakeholder Management: You are expected to present findings, explain

technical concepts in clear language and manage expectations throughout the

tenure.

● Documentation and Reporting: In addition to presenting findings and managing

expectations, you are required to document data sources, model architectures,

training procedures, evaluation metrics and deployment processes.

5. Regulatory Compliance and Ethical Considerations:

● Regulatory Compliance: Solutions you define may need to comply with various

regulatory standards and guidelines. Responsibilities related to ensuring

regulatory compliance, such as data protection laws (e.g., GDPR), industry

specific regulations (e.g., healthcare regulations) and ethical guidelines (e.g.,

IEEE Ethically Aligned Design.

● Ethical Considerations: You are also required to keep in mind issues such as bias

mitigation, fairness, transparency and privacy protection in AI systems that you

build.

6. Continuous Learning:

● Staying Current with AI Trends: You are responsible for staying up to date with

the latest advancements in algorithms, frameworks and ethical considerations

surrounding AI.

About xCroTek

xCroTek is a product- and service-based AI software company that builds innovative, AI-powered solutions to drive intelligent automation and digital transformation. We specialize in creating scalable, impactful technologies for modern businesses.

Job Overview

We are hiring a Generative AI Engineer with hands-on experience in LLMs and multi-agent frameworks. The ideal candidate will help us design, implement, and optimize next-gen AI systems, including Retrieval-Augmented Generation (RAG) pipelines, AI agents, and custom-trained models.

Key Responsibilities

• Design and implement AI pipelines using LLMs (e.g., GPT, LLaMA, DeepSeek, etc.)
• Develop AI agents using tools like AutoGen, CrewAI, and LangChain
• Work with RAG architectures for contextual response generation
• Create REST APIs using FastAPI or Flask
• Integrate vector databases (e.g., ChromaDB, Pinecone)
• Fine-tune and evaluate LLMs on domain-specific data
• Deploy models on cloud platforms (AWS, GCP, Azure)

Required Skills

• Strong Python programming skills
• Experience with web scraping and dataset preparation
• Familiarity with Hugging Face Transformers, PyTorch or TensorFlow
• Knowledge of embeddings, tokenization, and transformer-based models
• Hands-on experience in model optimization for performance and accuracy

Preferred Qualifications

• Certifications in Generative AI, Data Science, or Machine Learning
• Prior experience working on voice bots or NLP applications
• B.Tech / MCA/ M.Tech (Final-year students or recent graduates may also apply)

What We Offer:

• Competitive salary with performance-based bonuses.
• Opportunities for professional growth and learning.
• Work on impactful projects that contribute to advancements in AI & Technology.
• Remote working flexibility.
• Mentorship and support from experienced data analysts.

How to Apply:

Interested candidates should submit their resume and a brief cover letter explaining their interest in the role to Please include "Generative AI Engineer" in the subject line.

Deadline for applications: 10 August 2025

Apply with a one-page cover letter and CV to