AI/ML Practice Lead

Whereuelevate; India; On-site; INR 4,500,000 - 7,500,000; Full time

Job summary

Whereuelevate is looking for an experienced AI/ML Practice Lead to own end-to-end AI/ML and Generative AI solutioning for client opportunities and lead technical delivery. The role requires driving solution architecture, project estimates, governance, and team execution to build production-grade AI systems, with a focus on Generative AI, RAG architectures, and cloud-based AI platforms.

The ideal candidate will translate client requirements into scalable AI solutions and lead design reviews while

Qualifications

• 12–15+ years of overall experience
• 8–12+ years in AI/ML/GenAI engineering
• Strong experience in solution architecture and delivery leadership

Responsibilities

• Own end-to-end AI/ML and Generative AI solutioning for client opportunities
• Lead technical delivery including architecture, estimates, governance, and team execution
• Drive client solutioning, pre-sales and present to technical and business stakeholders
• Design reviews and architecture decisions; support sprint planning and engineering execution
• Build reusable assets and accelerators (reference architectures, templates, frameworks)

Skills

RAG architecture

LLM orchestration

LangChain / LangGraph

Solution architecture

Delivery leadership

Cloud AI platforms

Embeddings

MLOps/LLMOps

PostgreSQL

Redis

Kafka / Event Hubs

FastAPI

Data Platforms (ADLS / S3)

Vector Databases

Technical Delivery Leadership

Stakeholder management

Presenting to stakeholders

Tools

PostgreSQL

Redis

FastAPI

Job description

We are looking for an experienced AI/ML Practice Lead who will own end-to-end AI/ML and Generative AI solutioning for client opportunities and lead technical delivery. The role requires driving solution architecture, project estimates, governance, and team execution to build production-grade AI systems.

The ideal candidate will have strong expertise in Generative AI, RAG architectures, and cloud-based AI platforms, along with the ability to translate client requirements into scalable AI solutions.

Key Responsibilities

Client Solutioning & Pre-Sales

• Lead client discovery discussions and translate business requirements into solution architectures.
• Prepare SOW inputs, project timelines, and effort estimates for AI/ML engagements.
• Present technical solutions to technical and business stakeholders.

Design and review architectures for:

Generative AI / RAG Systems

• Chunking strategies
• Embeddings
• Vector databases (pgvector, Pinecone, Weaviate)
• Hybrid search and re-ranking
• Grounding techniques
• Tool/function calling
• Agent-based workflows
• Model training and inference pipelines

MLOps / LLMOps

• Model registry and versioning
• Canary deployments
• Drift monitoring
• Feedback loops

System Standards & Governance

• Define non-functional standards including:
• Latency and scalability
• Cost and token budgeting
• Observability (logs, metrics, traces)
• Reliability and fallback mechanisms

Security & Compliance

• Ensure secure AI deployments including:
• PII handling and data masking
• RBAC implementation
• Audit logging
• Private networking
• Secrets management

Technical Delivery Leadership

• Conduct design reviews and architecture decisions
• Support sprint planning and engineering execution
• Review code and pull requests
• Provide hands-on development support when required

Practice Development

• Build reusable assets and accelerators, including:
• Reference architectures
• Templates and frameworks

Requirements

Experience

• 12–15+ years of overall experience
• 8–12+ years in AI/ML/GenAI engineering
• Strong experience in solution architecture and delivery leadership

Technical Skills

• Hands-on experience with RAG and LLM orchestration frameworks such as LangChain or LangGraph
• Experience working with Cloud AI platforms (Azure / AWS / GCP / On-premise)

Data & Platform Experience

• Streaming platforms: Kafka, Event Hubs
• APIs and backend development using FastAPI
• Datastores such as PostgreSQL and Redis

Additional Requirements

• Proven experience taking AI/ML solutions from POC to production
• Strong stakeholder management and communication skills
• Ability to present complex AI solutions to both technical and business audiences

Skills required

• AI
• ML
• GenAI
• LLM
• RAG
• Technical Solution Design
• LangChain / LangGraph
• Prompt Engineering
• Embeddings
• Hybrid Search / Re-ranking
• MLOps/LLMOps
• APIs (FastAPI)
• Data Platforms (ADLS / S3)
• Kafka / Event Hubs
• Redis
• Vector Databases

Locations

• Noida
• Pune