Data Scientist

On-siteSeniorAI Engineerposted 2w ago

✦Role summaryAI-generated

This senior AI engineer will lead the design and deployment of agentic AI workflows using LangGraph, AutoGen, and LangChain, building scalable REST/WebSocket APIs and integrating LLMs into enterprise applications. They will manage production GenAI projects, integrate SQL/NoSQL/vector databases, and mentor cross‑functional teams to ensure secure, compliant AI solutions.

About this role

Lead the design and implementation of agentic AI workflows using LangGraph, AutoGen, LangChain, or similar frameworks.
Architect and optimize scalable APIs (REST/WebSocket) for production deployment.
Develop, fine-tune, and integrate large language models into enterprise applications.
Deploy and maintain at least 3 GenAI/Agentic AI projects in production, ensuring reliability, scalability, and performance.
Integrate SQL, No-SQL, and vector databases such as Postgres, MongoDB, and ChromaDB.
Implement graph databases (Neo4j) for knowledge graph-based use cases.
Provide technical leadership and mentorship to engineering teams.
Collaborate with cross-functional stakeholders to identify and deliver GenAI solutions across multiple business domains.
Ensure robustness, security, and compliance of deployed AI systems.
Stay current with trends in GenAI, deep learning, and orchestration frameworks.
Document and present technical solutions to both technical and non-technical audiences.
Familiarity with LangGraph, AutoGen, LangChain, or similar agentic AI frameworks.
Experience with multi-agent systems and orchestration of intelligent workflows.
Knowledge of MLOps practices (CI/CD, model monitoring, retraining pipelines).
Strong problem-solving skills and ability to thrive in fast-paced R&D environments.
Contributions to open-source AI/ML projects or published research in generative AI.

Responsibilities

Coordinate team tasks, assist in project management, handle customer inquiries, and prepare reports.

Bachelor’s or Master’s degree in Computer Science, Data Science, Data Engineering, AI/ML, or related field.
4+ years of total professional experience in AI/ML, Data Science, or related fields.
3+ years of hands-on experience in Python with strong software engineering practices.
At least 3 years of experience in AI/ML engineering, including 2+ years of hands-on experience in Generative AI /Agentic AI.
Hands-on experience with deep learning frameworks (PyTorch, TensorFlow).
Expertise in large language models (LLMs), prompt engineering, and fine-tuning.
Proven track record of deploying at least 3 GenAI/Agentic AI projects into production.
Strong background in Data Science or Data Engineering, including data pipelines, ETL, and data modeling.
Practical knowledge of SQL, No-SQL, vector databases, and graph databases.