Deployment Engineer

Avig Business Solutions; Pune District, Chennai District, Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Avig Business Solutions in Pune seeks a Forward Deployed Engineer who embeds with client teams to map complex workflows and engineer autonomous AI-agent solutions.

You will own the solution lifecycle from discovery to deployment, bridging agentic architectures with real business outcomes. Strong production experience with LLMs, API design, and cloud deployment is required.

Qualifications

• Production-grade software development experience.
• LLM agents, skill-building architectures, or RAG pipelines in production.
• Ability to own projects end-to-end with minimal guidance.
• Excellent client-facing communication and requirement gathering.

Responsibilities

• Partner with business stakeholders to map manual processes into agentic workflows.
• Design, build, and deploy multi-agent systems and function-calling pipelines.
• Develop production-ready backend services and integration layers with enterprise platforms.
• Package, host, and scale agent workloads on cloud infrastructure with CI/CD.
• Implement guardrails and human-in-the-loop checkpoints for reliability.

Skills

Python

LLM Agents

Cloud

DevOps

APIs

Agentic AI

Education

Bachelor's degree in Computer Science

Tools

FastAPI

Docker

GitHub Actions

SQL

Pinecone

Job description

We are looking for a Forward Deployed Engineer (FDE) who thrives at the intersection of cutting-edge AI technology and real-world business execution. In this role, you won't just write code in a silo—you will embed directly with client teams, map complex and manual workflows, and engineer autonomous AI-agent solutions to replace them.

You will own the solution lifecycle end-to-end: discovery, architecture, build, deployment, and iteration. Working with minimal direction, you’ll serve as the technical authority who bridge the gap between complex agentic architectures and high-impact business outcomes.

Key Responsibilities

• Client Embedding & Workflow Discovery: Partner directly with business stakeholders to break down manual enterprise processes, map complex decision-making steps, and translate them into robust agentic workflows.
• Agentic AI Engineering: Design, build, and deploy custom multi-agent systems, function-calling pipelines, RAG implementations, and reusable agent skills.
• End-to-End System Ownership: Develop production-ready backend services and integration layers to connect AI agents with core enterprise platforms (e.g., SharePoint, Jira, SAP, email).
• Cloud & Infrastructure Management: Package, host, and scale agent workloads using modern cloud architectures (AWS AgentCore, serverless, containerized environments) with automated CI/CD.
• Safety & Observability: Implement guardrails, human-in-the-loop checkpoints, and agent evaluation loops to ensure reliability, mitigate hallucinations, and ensure enterprise compliance.

Technical Requirements

Agentic AI & LLMs

• Frameworks: Hands-on experience with Strands (primary framework), along with familiarity in LangGraph, CrewAI, or AutoGen.
• Agent Core Concepts: Deep understanding of tool use, function calling, streaming, context management, system prompts, and chain-of-thought methodologies.
• MCP & Agent Protocols: Proven ability to build/consume Model Context Protocol (MCP) servers, alongside multi-agent coordination (A2A), task delegation, and result aggregation.
• RAG Pipelines: Hands-on build experience with vector databases (e.g., Pinecone, pgvector, OpenSearch), chunking strategies, embeddings, and retrieval optimization.
• Skill Building & Guardrails: Design reusable skills for agent consumption; implement observability, hallucination mitigation, and human-in-the-loop checkpoints.

Backend Development & Data

• Python Mastery: Strong experience with Python 3.10+ using async/await and strict type hinting.
• APIs & Web Frameworks: Proficiency with FastAPI (or equivalent), REST API design, and modern auth flows (JWT / OAuth2).
• Data Processing: Solid SQL skills (queries, filters, joins) and expertise in unstructured data processing (extracting/classifying data from PDFs, Excel, and legacy enterprise documents).

Infrastructure & DevOps

• AWS & Hosting: Experience hosting/operating agent workloads using AWS AgentCore (understanding lifecycle, scaling, and invocation patterns) along with core services (EC2/ECS, Lambda, RDS, S3).
• Containers & CI/CD: Docker proficiency and experience setting up GitHub Actions pipelines.

Qualifications & Experience

• Software Engineering Track Record: Strong foundation in core software engineering principles and production-grade software development.
• Production LLM Experience: At least one production project successfully delivered using LLM agents, skill-building architectures, or RAG pipelines.
• End-to-End Ownership: Demonstrated ability to drive projects independently from zero to one with minimal guidance.
• Client-Facing Communication: Comfortable interfacing with non-technical business partners—gathering requirements, explaining technical decisions, and presenting live solutions.