5 Code Quality jobs in India

We are seeking for a candidate with 4-8 years of experience in cyber security testing, specifically within the Banking, Financial Services, and Insurance (BFSI) sector. The ideal candidate will also have hands-on experience with DevOps practices. This role involves reviewing and auditing application code to identify security flaws, recommending remediation strategies, and ensuring adherence to secure coding guidelines.

Candidate Requirements

1. Bachelor's/Master's degree in Computer Science, Information Technology, or a related field
2. 4-8 years of experience in software development, with a focus on the BFSI sector
3. Proficient in one or more programming languages such as Java, C#, .NET, or Python
4. Hands-on experience with DevOps tools and practices, including CI/CD pipelines, containerization (Docker), and orchestration (Kubernetes)
5. Strong understanding of BFSI industry processes, regulations, and standards
6. Experience with database management systems such as SQL Server, Oracle, or MySQL
7. Knowledge of software development methodologies, such as Agile and DevOps
8. Familiarity with security standards and practices relevant to the BFSI sector, including encryption, data masking, and regulatory compliance
9. Strong problem-solving skills and attention to detail
10. Excellent communication skills and the ability to work effectively in a team environment

Key Responsibilities and Outcomes

1. Conduct secure code reviews for applications developed in .NET and Java to identify security vulnerabilities
2. Utilize OWASP Top 10 guidelines to analyze and mitigate common security risks such as SQL injection, cross-site scripting (XSS), and cross-site request forgery (CSRF)
3. Collaborate with development teams to integrate secure coding practices into the software development lifecycle (SDLC)
4. Provide actionable recommendations and guidance on code remediation to developers
5. Develop and maintain secure coding standards and best practices documentation
6. Assist in the development and implementation of security tools and automated code review processes
7. Stay up-to-date with the latest security trends, vulnerabilities, and technology developments
8. Conduct security training and awareness sessions for development teams
9. Participate in security assessments and penetration testing as needed

Hiring a Technical Reviewer on behalf of a leading AI lab to evaluate and refine benchmarking pipelines for reinforcement learning (RL) environments and agentic AI systems. In this role, you'll be responsible for
reviewing environment design, terminal conditions, and evaluation protocols
to ensure accuracy, reproducibility, and fairness in benchmarking. You'll work closely with researchers and engineers to provide technical feedback that strengthens experimental rigor and system reliability.

You're a Great Fit If You

• Have a background in reinforcement learning, computer science, or applied AI research.
• Are experienced with RL environments.
• Understand benchmarking methodologies, terminal conditions, and evaluation metrics for RL tasks.
• Are comfortable reading and reviewing codebases in Python (PyTorch/TensorFlow a plus).
• Have strong critical thinking skills and can provide structured technical feedback.
• Care deeply about experimental reproducibility, fairness, and standardization in agentic AI.
• Are detail-oriented and capable of reviewing both theoretical formulations and implementation details.

Primary Goal Of This Role
To review, validate, and improve reinforcement learning environment benchmarking pipelines, ensuring that terminal conditions, evaluation metrics, and system behaviors are robust, reproducible, and aligned with agentic AI research goals.

What You'll Do

• Review RL environments and evaluate terminal conditions for correctness and consistency.
• Assess benchmarking pipelines for fairness, reproducibility, and alignment with research objectives.
• Provide structured technical feedback on code implementations and documentation.
• Collaborate with researchers to refine evaluation metrics and methodologies.
• Ensure reproducibility by validating results across different runs, seeds, and hardware setups.
• Document findings and recommend improvements for environment design and benchmarking standards.

Why This Role Is Exciting

• You'll directly influence the reliability of benchmarking in agentic AI research.
• You'll work on cutting-edge RL environments that test the limits of intelligent agents.
• You'll help establish standards for evaluation and reproducibility in a fast-moving field.
• You'll collaborate with researchers shaping the future of agentic AI systems.

Skills: agentic ai,benchmarking,research,python,reinforcement,tensorflow,terminal,pytorch,code review,code

We have an opportunity of Team Member - Quality Assurance . If you are interested for the position, kindly fill up the link.

We have an opportunity of Team Member - Quality (NPD) . If you are interested for the position, kindly fill up the link.