GenAI Engineer

Role Summary

We are seeking a GenAI Engineer / Architect to design and deliver enterprise-grade AI solutions including RAG pipelines, AI agents, orchestration frameworks, and governance models.

The role involves building scalable, production-ready GenAI systems using modern LLM platforms like Microsoft Azure OpenAI and integrating them into enterprise ecosystems.

Key Responsibilities GenAI Solution Architecture

• Design end-to-end GenAI solutions using LLMs, RAG, embeddings, and vector search.
• Define scalable architectures for enterprise AI applications.

RAG & Search Systems

• Build RAG pipelines (chunking, embeddings, retrieval, ranking).
• Work with vector databases such as Azure AI Search, Redis, PostgreSQL.
• Implement citation validation and hallucination detection mechanisms.

Agentic AI & Orchestration

• Design and develop AI agents and multi-agent systems.
• Implement orchestration workflows using tools like Workato, AWS services, DigitalNet.
• Build AI-driven automation pipelines.

Document Intelligence

• Develop document ingestion pipelines (OCR, metadata extraction, enrichment).
• Handle structured and unstructured data processing.

Cloud & Deployment

• Deploy AI workloads on Azure (OpenAI, AI Search, ML, AKS).
• Work across multi-cloud environments (Azure, AWS).
• Implement CI/CD pipelines and DevSecOps practices.

Responsible AI & Governance

• Implement Responsible AI frameworks (fairness, bias, explainability).
• Align with standards like NIST AI RMF and enterprise governance tools (CredoAI).

Leadership & Collaboration

• Lead POCs, solution evaluations, and technical documentation.
• Collaborate with cross-functional teams and stakeholders.

Required Skills GenAI & LLMs

• Strong experience in:

• RAG architectures

• Prompt engineering & evaluation

• LLM platforms (Azure OpenAI, Claude, Gemini)

• Hallucination detection & response validation

AI Engineering

• Experience building AI agents and orchestration frameworks.
• Knowledge of LangChain / agent frameworks (preferred).

Data & Search

• Experience with vector databases:

• Azure AI Search

• Redis

• PostgreSQL

Document Processing

• Experience with OCR, metadata extraction, document pipelines.

Cloud & DevOps

• Strong experience with:

• Azure & AWS

• Kubernetes (AKS)

• CI/CD & DevSecOps

Governance

• Experience with:

• Responsible AI frameworks

• AI governance tools (e.g., CredoAI)

• Compliance frameworks (e.g., NIST AI RMF)

Required Certifications

• Azure AI Fundamentals (AI-900)
• Azure Data Fundamentals (DP-900)
• Responsible AI certifications
• AWS Machine Learning Specialty
• TensorFlow Developer Certification
• Kubernetes (CKA/CKAD)
• SAFe Agile Certification (ASE preferred)

Preferred Certifications

• Azure AI Engineer (AI-102)
• Azure Data Scientist (DP-100)
• Azure Solutions Architect (AZ-305)
• Azure Developer (AZ-204)

Skills: aws,azure openai,langchain,azure,ci/cd,nist framework,llm,gen ai,ocr,azure certification,credoai