Gen AI architect

About the Company

AI/GEN AI Architect

About the Role

4+ years of experience in AI/ML, with 2+ years in GenAI or LLM-based solutions. Define and lead the architecture of GenAI solutions across multiple business domains.

Responsibilities

• Deep understanding of:
• RAG architectures (vector stores, retrieval strategies, reranking)
• Prompt engineering patterns (system prompts, templates, structured output)
• Agents and tool-use (planning, memory, tool calling, guardrails)
• Hands-on proficiency in Python
• Experience with frameworks such as LangChain / LlamaIndex / Semantic Kernel (or equivalent orchestration libraries)
• API development experience with FastAPI / Flask / Spring Boot / Node.js
• Strong experience with at least one cloud: Azure / AWS / GCP
• Exposure to services like:
• Azure: Azure OpenAI, Cognitive Search, AKS, Functions
• AWS: Bedrock, OpenSearch, Lambda, EKS
• GCP: Vertex AI, Vector Search, Cloud Run/GKE
• Exposure to Containerization and CI/CD: Docker, Kubernetes, pipelines (Azure DevOps/GitHub Actions/Jenkins)
• Experience with vector databases (Pinecone, Milvus, Weaviate, FAISS) and/or search engines (Elastic/OpenSearch)
• Strong SQL fundamentals; familiarity with document stores and metadata catalogs is a plus
• Ability to evaluate and select appropriate LLMs, frameworks, and infrastructure for GenAI use cases
• Good to have fine-tuning experience: LoRA/PEFT, instruction tuning, embeddings tuning
• Strong architectural thinking; ability to simplify complexity for senior stakeholders
• Excellent communication and documentation skills (HLD/LLD, reference architecture, ADRs)
• Ability to lead cross-functional teams and drive consensus
• Outcome-driven mindset: links technology to business value and KPIs
• Should be able to stay ahead of emerging trends in GenAI, LLMs, and multimodal AI to guide innovation
• Cloud certifications (Professional / Architect level)

Qualifications

4+ years of experience in AI/ML, with 2+ years in GenAI or LLM-based solutions.

Required Skills

• Hands-on proficiency in Python
• Strong experience with at least one cloud: Azure / AWS / GCP
• Strong SQL fundamentals
• Excellent communication and documentation skills

Preferred Skills

• Experience with frameworks such as LangChain / LlamaIndex / Semantic Kernel
• Good to have fine-tuning experience: LoRA/PEFT, instruction tuning, embeddings tuning
• Familiarity with document stores and metadata catalogs

Pay range and compensation package

Not specified.

Equal Opportunity Statement

We are committed to diversity and inclusivity.