Job Description

- Agentic AI Solutions Consultant

Type:

Consulting / Contract (part-time or full-time negotiable)

Location:

Remote or hybrid

Duration:

Initial 6 months, extendable

Compensation:

Competitive, based on expertise

Work Timing:

Candidate must be available 3:00 PM - 12:00 AM IST

Role Summary

We are seeking an

Agentic AI Solutions Consultant

to lead our adoption of agentic AI technologies. The role requires deep

hands-on expertise in LLM systems, multi-agent orchestration, and the Model Context Protocol (MCP)

, along with the ability to mentor and guide our internal engineering team.

You will design and implement agent-driven architectures, integrate them with enterprise applications, web platforms, and cloud services, and establish best practices for AI reliability, safety, and governance. The solutions will be applied in web applications initially, with the scope to extend into mobile applications in the future.

Key Responsibilities

Agentic AI Implementation

Design and deploy multi-agent systems capable of tool use, task routing, retries/backoff, and stateful memory.

Model Context Protocol (MCP)

Implement MCP servers/tools or clients to enable structured, context-aware agent interactions.

RAG Pipelines

Build Retrieval-Augmented Generation flows with vector databases (pgvector, Pinecone, Weaviate, Milvus, FAISS).

Systems Integration

Connect AI agents with enterprise applications, developer platforms, collaboration tools, and cloud services.

Reliability & Safety

Define and enforce guardrails, evaluation frameworks, observability, and cost/performance tracking.

Coaching & Enablement

Mentor engineers through workshops, design reviews, and playbooks to accelerate AI adoption.

Strategic Input

Provide leadership input on the AI roadmap, from proof-of-concepts to scalable production systems.
Required Skills & Experience

AI Service Development (Python or TypeScript)

Recent, hands-on experience building and deploying LLM-backed services in Python (FastAPI/Flask) or TypeScript/Node.js (Express/NestJS/Next.js).

Agent Frameworks

Practical experience with LangChain or LlamaIndex (Python or TypeScript). Exposure to AutoGen or CrewAI is a plus.

Model Context Protocol (MCP)

Hands-on implementation of MCP servers/tools or clients in Python or TypeScript.

Multi-Agent Orchestration

Proven design and operation of agent workflows (tooling, coordination, retries, state persistence).

RAG & Vector Databases

Production experience with RAG pipelines and at least one vector store (pgvector, Pinecone, Weaviate, Milvus, FAISS).

AI Safety & Reliability

Guardrails, evaluation frameworks, prompt/version management, observability, and cost/performance tuning.

Cloud & Data Integration

Experience deploying containerized AI services on AWS ECS, Lambda, SQS, S3, Aurora and integrating with databases (relational/document).

Enterprise & Tool Integration

Proven ability to connect AI systems with developer platforms (e.g., GitHub, CI/CD), collaboration tools (e.g., chat platforms), and enterprise applications.

Observability Systems

Experience working with logging and monitoring platforms (ELK, Prometheus, Grafana, or equivalents).

Web Applications

Demonstrated experience integrating AI services into web applications.
Preferred Qualifications

Experience with integrating AI services into mobile applications is a plus. Familiarity with CI/CD pipelines and Docker-based deployments. Exposure to AI use-cases in financial services, CRM, or workflow automation.
Job Type: Contractual / Temporary
Contract length: 6 months

Pay: ₹541,938.27 - ₹1,260,749.20 per year

Application Question(s):

Are you comfortable with the Work timing (3 PM - 12 AM, Monday to Friday)? What is your current salary package (in hand after all deductions)? What is your expected salary package (in hand after all deductions)? How soon can you join if selected? You can provide the Notice Period with your current employer.
Work Location: In person