AI Systems Engineer (LLM + Workflow Orchestration)

Forage AI; India; On-site; INR 2,000,000 - 2,800,000; Full time

Job summary

Forage AI is seeking a hands-on AI Systems Engineer to design and deploy end-to-end AI/ML solutions into production. You will build agentic systems that reason, act, and operate autonomously through structured workflows.

You’ll mentor junior AI developers, ensure high-quality execution, and collaborate closely with the team to deliver scalable, cloud-ready AI architectures using LangChain, LangGraph, and related tools.

Qualifications

• 3–5+ years of experience in AI/ML Engineering or AI Systems Development.
• Hands-on experience building and deploying production-grade AI systems.
• Strong foundation in LangChain and LangGraph.
• Experience designing or building an agentic framework or workflow system from scratch.
• Strong algorithmic thinking and problem‑solving skills.
• Proficiency in Python and backend frameworks.

Responsibilities

• Design and build agentic AI systems with multi-step reasoning and workflow orchestration.
• Develop and deploy end-to-end AI/ML pipelines from ideation to production.
• Architect multi-agent workflows with memory, tool usage, and decision logic.
• Work with frameworks like LangChain, LangGraph, and similar ecosystems.
• Build systems integrating LLMs with APIs, databases, and external tools.
• Implement evaluation, validation, and fallback strategies.
• Collaborate with junior AI developers and mentor them.
• Guide and support teammates on development tasks.

Skills

LangChain

LangGraph

Agentic tools

Agentic framework design

Python

Backend frameworks

AI/ML Engineering

Mentoring

Education

Bachelor’s degree in Computer Science

Master’s degree in Artificial Intelligence

Tools

AWS

Azure

OpenClaw

Job description

Forage AI builds next-generation systems for large-scale data collection and processing — including web crawling, document parsing, enrichment pipelines, and automation. We primarily work in Python, design cloud-native systems (AWS-first, with exposure to GCP/Azure), and increasingly integrate GenAI and agent-based workflows into our stack.

Our engineering culture emphasizes ownership, clarity, and reliability. Every developer owns their module end-to-end and collaborates closely in a high-trust, high-impact environment.

About the Role

We’re looking for a hands-on AI Systems Engineer who has built and deployed end-to-end AI/ML solutions into production. This role goes beyond applied AI—you’ll design agentic systems that can reason, act, and operate autonomously through structured workflows.

You’ll also play a key role in mentoring junior AI developers, ensuring high-quality execution and accelerating team capability.

Key Responsibilities

Design and build agentic AI systems with multi-step reasoning and workflow orchestration.

Develop and deploy end-to-end AI/ML pipelines from ideation to production.

Architect multi-agent workflows with memory, tool usage, and decision logic.

Work with frameworks like LangChain, LangGraph, and similar ecosystems.

Build systems integrating LLMs with APIs, databases, and external tools.

Implement evaluation, validation, and fallback strategies.

Team Responsibilities

Work closely with and be tagged with junior AI developers on projects.

Assist, guide, and handhold junior team members in development tasks.

Act as a go-to person for quickly resolving technical queries.

Monitor progress and ensure best practices in AI system development.

Must-Have Skills

3–5+ years of experience in AI/ML Engineering or AI Systems Development

Hands-on experience building and deploying production-grade AI systems

Strong foundation in:

• Proven experience with:
• o LangChain
• o LangGraph
• o Experience with agentic tools/frameworks (e.g., OpenClaw or similar ecosystems)
• Experience designing or building an agentic framework or workflow system from scratch
• Strong algorithmic thinking and problem‑solving skills
• Proficiency in Python and backend frameworks

Education

Bachelor’s degree in Computer Science or

Master’s degree in Artificial Intelligence / related field

Nice to Have

Experience with cloud platforms such as Amazon Web Services or Microsoft Azure (including ML Studio or equivalent)

Experience deploying scalable AI systems in cloud environments

Published research papers or patents in Agentic AI / LLM systems

Exposure to advanced AI system design or multi‑agent collaboration frameworks

What Sets You Apart

You’ve built systems where agents take actions—not just generate outputs

You think in workflows, pipelines, and systems, not isolated models

You’ve mentored or led junior engineers and enjoy enabling others

You’ve handled real-world production challenges (scaling, failures, optimization).

Why Join

Build cutting‑edge agentic AI systems (not just surface-level AI work)

High ownership and opportunity to architect systems from scratch

Collaborative environment with real technical depth