AI/ML Agentic-Workflows Engineer

Proven success delivering AI and agentic products from concept to adoption, with hands-on design of real-time ML systems.
Experience with GenAI, LLMs, NLP, RAG, and Knowledge Graphs across the ML lifecycle (train, optimize, deploy, monitor).
Expertise in multi-agent systems and frameworks like LlamaGraph or LangChain for complex workflows.
Proficiency deploying and scaling ML/agentic solutions in cloud environments (e.g., AWS).
Passion for rapid iteration and high-quality execution with an entrepreneurial mindset.
BS in CS or equivalent, 5-10 years of experience; MS/PhD preferred.

Provide hands-on technical leadership to design, develop, optimize and deploy Generative AI features, leveraging expertise in LLMs, RAGs, NLP, and AI infrastructure to optimize Agents quality, reliability and performance.
Support and Lead a strong technical team across the US and Bangalore, guiding them on state-of-the-art approaches to ML system design, Agent design and orchestration while establishing the best in class data-driven development practices.
Build agents that streamline data extraction, transformations and analysis.
Define scalable evaluation strategies that balance AI with human reviewers.

ML/LLM work in code generation (e.g., Codex, text-to-SQL), semantic extraction, or knowledge graphs (e.g., Neo4j, Neptune).
Experience with big-data engines like Spark.
Compiler development for languages like SQL, Python, or Scala.
Optimization of ML models for low-latency, high-throughput production use.
Contributions to open-source AI/ML projects (e.g., Hugging Face, PyTorch).
Expertise in retrieval systems or vector databases (e.g., Pinecone, Weaviate).
Skill in evaluating tech and driving build/buy decisions.