Generative AI Engineer

About us:

At Dabster, we are your one-stop destination for talent acquisition and digital innovation. Our customized, scalable talent solutions empower organizations to concentrate on their core business while we expertly match the right talent to the right roles.

Who will you work with:

A global technology firm enabling next‑generation digital transformation through deep expertise in cloud, AI, data and enterprise solutions. With a strong focus on engineering-led delivery and long-term customer partnerships, the organization drives measurable business outcomes through innovative, enterprise-grade solutions.

Job Description:

We are looking for a hands-on Generative AI and Agentic AI expert who can own end‑to‑end solution design and delivery for complex, real-world enterprise use cases. You will work closely with architects and business stakeholders to turn problem statements into scalable, production-grade AI solutions.

Must have:

• 10+ years of overall experience, primarily in data science, AI/ML, GenAI and NLP technologies.
• Minimum 2+ years of hands-on GenAI application development.
• Strong problem-solving skills and ability to design and implement technical solutions independently.

Technical skills:

• Practical experience with Agentic AI frameworks and concepts such as LangGraph, LlamaIndex, function calling, tools registry, intent-based routing, Chain-of-Thought, MCP and multi‑agent systems.
• Deep experience using both paid (OpenAI on Azure, AWS Bedrock, other leading providers) and open-source LLMs, VLMs and SLMs.
• Strong expertise in RAG, CAG, Knowledge Graph RAG, RAG Fusion, agents, NLQ‑to‑SQL and related patterns.
• Experience working with large unstructured datasets (multiple file formats) as well as structured data (data lakes).
• Hands-on experience with leading vector databases, chunking strategies and graph databases (e.g. Neo4j).
• Experience with MarkLogic / NoSQL databases and Elasticsearch, plus solid understanding of RDBMS (e.g. PostgreSQL) and data lakes.

Engineering & MLOps:

• Strong Python skills with the ability to write clean, efficient code; experience with FastAPI for building and exposing services/APIs.
• Knowledge of at least one additional programming language.
• Solid understanding of model development, serving, training and re‑training techniques, including in data‑sparse environments.
• Experience deploying solutions on AWS and/or Azure, including Kubernetes and serverless-based deployments.
• Experience enforcing and using reusable components across multiple solutions.
• Experience developing guardrails for LLMs using both open-source and cloud-native tools.

How to apply:

If your expertise meets the above job, we would love to hear back from you, kindly share your resume to [email protected]