Posted 11 July, 2026
AI Engineer
Diverse Lynx
Bangalore
Full Time
Reference: 365_569689_26-01266
Role Overview: Design, develop, and deploy scalable AI/ML and GenAI solutions to solve complex business problems. Work closely with data scientists, business stakeholders, and cloud teams to build production-grade AI systems.
Key Responsibilities:
· Drive technical direction for agentic AI initiatives, influencing architecture patterns, autonomy boundaries, and system design.
· Design, build, and operate production-grade agentic AI systems used across multiple products.
· Own and evolve shared agentic AI capabilities, including:
· Design and Develop Agent frameworks and orchestration layers
· Planning, tool use, and memory strategies
· Design Retrieval and grounding (RAG) pipelines
· LLM infrastructure, inference, and model gateways
· Evaluation, observability, and safety tooling for autonomous systems
· Lead technical design reviews and help teams navigate tradeoffs involving autonomy, safety, reliability, scalability, and cost.
· Partner across teams to deliver complex, cross-cutting agentic AI initiatives from concept to production.
· Evaluate emerging models, techniques, and agentic patterns and translate them into practical, enterprise-ready improvements.
Technical Skills:
· 6+ years of experience building large-scale distributed systems + strong experience with LLM systems, agentic workflows or advanced ML infrastructure, async processing, queues, and streaming systems
· Advanced proficiency in Python, Hands-on experience with PyTorch, TensorFlow, Hugging Face.
· Practical knowledge of model orchestration frameworks (e.g., LangChain, LlamaIndex, CrewAI), Familiarity with vector databases
· Experience with cloud platforms (AWS, Azure AI, Google Cloud Vertex AI) and containerization technologies
· Proven ownership of complex, cross-cutting agentic systems spanning multiple teams or products.
· Strong engineering fundamentals across backend systems, APIs, data pipelines, and cloud infrastructure.
· Deep experience across the agentic AI stack, including planning, tool use, memory, and evaluation.
· Fluency with AI-assisted and agentic development workflows.
· Ability to influence technical direction and align teams without formal authority.
· Problem-solving, cross-functional collaboration, and the ability to articulate complex AI concepts to non-technical business stakeholders
Key Responsibilities:
· Drive technical direction for agentic AI initiatives, influencing architecture patterns, autonomy boundaries, and system design.
· Design, build, and operate production-grade agentic AI systems used across multiple products.
· Own and evolve shared agentic AI capabilities, including:
· Design and Develop Agent frameworks and orchestration layers
· Planning, tool use, and memory strategies
· Design Retrieval and grounding (RAG) pipelines
· LLM infrastructure, inference, and model gateways
· Evaluation, observability, and safety tooling for autonomous systems
· Lead technical design reviews and help teams navigate tradeoffs involving autonomy, safety, reliability, scalability, and cost.
· Partner across teams to deliver complex, cross-cutting agentic AI initiatives from concept to production.
· Evaluate emerging models, techniques, and agentic patterns and translate them into practical, enterprise-ready improvements.
Technical Skills:
· 6+ years of experience building large-scale distributed systems + strong experience with LLM systems, agentic workflows or advanced ML infrastructure, async processing, queues, and streaming systems
· Advanced proficiency in Python, Hands-on experience with PyTorch, TensorFlow, Hugging Face.
· Practical knowledge of model orchestration frameworks (e.g., LangChain, LlamaIndex, CrewAI), Familiarity with vector databases
· Experience with cloud platforms (AWS, Azure AI, Google Cloud Vertex AI) and containerization technologies
· Proven ownership of complex, cross-cutting agentic systems spanning multiple teams or products.
· Strong engineering fundamentals across backend systems, APIs, data pipelines, and cloud infrastructure.
· Deep experience across the agentic AI stack, including planning, tool use, memory, and evaluation.
· Fluency with AI-assisted and agentic development workflows.
· Ability to influence technical direction and align teams without formal authority.
· Problem-solving, cross-functional collaboration, and the ability to articulate complex AI concepts to non-technical business stakeholders
