1 month ago
Bengaluru, IndiaSenior
Responsibilities
- Design, build, deploy, debug, and optimize agentic AI systems using LLMs, tool orchestration, and multi-agent workflows.
- Develop MLOps pipelines, RAG systems, vector database and retrieval strategies, prompt frameworks, evaluation pipelines, and safety guardrails.
- Integrate LLM-based systems with enterprise APIs, data platforms, and operational systems.
- Implement observability, feedback loops, and performance monitoring for production agentic systems.
- Shape technical solutions, validate approaches, create solution blueprints, and translate ambiguous business problems into robust architectures.
- Provide technical oversight across multiple client engagements and guide engineers and data scientists while remaining hands-on with code.
- Contribute to pre-sales conversations and establish technical standards for the AI practice.
Requirements
- 6–8 years of professional software engineering experience involving Agentic AI, plus 5+ years of hands-on experience with generative AI and LLM-based systems in production.
- Bachelor's or master's degree in Computer Science, IT, Electronics Engineering, Data Science, Machine Learning, AI Engineering, or a related field.
- Strong Python skills and experience with common data and machine learning libraries.
- Solid grounding in data science and machine learning, including practical experience with LLMs, generative AI, prompting, and RAG.
- Familiarity with building and orchestrating AI agents and evaluating production agent systems.
- Strong engineering habits, clear communication, and collaborative teamwork.
- Preferred qualifications include exposure to cloud AI platforms, Azure, MLOps, LLMOps, mentoring junior colleagues, consulting, and client-facing delivery.
Benefits
- The company emphasizes an inclusive environment focused on diversity, belonging, respect, and contribution.
- Accommodation support is available for applicants with disabilities during the careers website and hiring process.