Senior Engineer, Agentic AI & MLOps Engineering (5-8 years)
On-siteBengaluru, Karnataka, India
Job Summary
Design, build, and deploy agentic AI systems using LLMs, tool orchestration, and multi-agent workflows while structurally debugging production issues and optimizing MLOps pipelines. Evaluate agents to ensure robust system behavior, develop prompt frameworks with guardrails, and integrate LLM-based systems with enterprise APIs and data platforms. Implement observability, feedback loops, and performance monitoring for agentic systems in production. You will shape solutions, validate technical approaches, and provide technical oversight across multiple client engagements, remaining close to the code to prototype and set credible technical examples. This hands-on architectural role requires 6–8 years of experience in software engineering and 5+ years with generative AI and LLM-based systems in production environments.
Required Qualifications
- Strong hands-on engineer who can Design, build, and deploy agentic AI systems using LLMs, tool orchestration, and multi-agent workflows
- Experience building multi-agent systems or autonomous workflows
- Proven expertise to structurally debug the AI production issue and apply the right fix
- Experience evaluating the Agents so that the production system remain robust
- Develop and optimize MLOps pipelines, RAG, vector databases and retrieval strategies
- Build robust prompt frameworks, evaluation pipelines, and guardrails for safe and reliable AI behaviour
- Integrate LLM-based systems with enterprise APIs, data platforms, and operational systems
- Implement observability, feedback loops, and performance monitoring for agentic systems in production
- 6–8 years of professional experience in software engineering with Agentic AI, ML platform engineering with 5+ years of hands-on experience with Generative AI and LLM-based systems in production environments
- BE/B.Tech/ME/M.Tech Computer Science/IT/Electronics Engg/ Data Science/ Machine learning/AI Engineering or related field
- Solid grounding in core data science and machine learning
- Practical experience with LLMs and generative AI, including prompting and RAG
- Familiarity with how AI agents are built and orchestrated
- Strong Python and common data/ML libraries; good engineering habits
- Clear communicator and collaborative team player
Desired Qualifications
- Exposure to cloud AI platforms, Azure a plus
- Experience practicing MLOps and LLMOps
- Early experience mentoring junior colleagues
- Interest in consulting and client-facing delivery
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