Description

You will architect and maintain end-to-end SDLC solutions focused on AI Agents, integrating AI-driven quality checks into CI/CD pipelines.

This role is hybrid.

Responsibilities

• Design and implement AI agents to autonomously analyze requirements, generate test scenarios, and identify defects early in the cycle.
• Partner with DevOps and SRE teams to integrate AI-driven quality checks into CI/CD pipelines.
• Establish and maintain MLOps practices for the AI lifecycle, automating processes across the engineering pipeline.
• Provide technical guidance and mentorship to develop Agentic AI driven quality solutions across multiple SDLC phases.
• Lead innovation pilots and POCs, evaluating emerging AI/ML tools and recommending adoption strategies.

Required Skills

• 10+ years of experience in software engineering.
• 3+ years applying AI/ML or GenAI solutions to develop workflows.
• Deep understanding of LLM models, Agentic AI concepts (LLM orchestration, autonomous agents, RAG, prompt engineering, vector DBs).
• Experience with Python, Java, C++, Scala, and Spark.
• Experience working with relational SQL and NoSQL databases.
• Knowledge of cloud platforms, including Azure or AWS.
• Hands-on experience with DataBricks.
• Expertise in standard software engineering methodology: test automation, CI, and code reviews.
• Experience with distributed systems and designing APIs.

Preferred Skills

• Experience with Hadoop and Kafka.
• Any Graduate education background.

Key Skills

Education

Any Graduate