Forward Deployed Engineer

Ciklum; Pune District, Chennai District, Bengaluru; On-site; INR 2,400,000 - 4,000,000; Full time

Job summary

Ciklum is seeking a Forward Deployed Engineer to embed with client teams, map complex enterprise workflows, and engineer autonomous AI-agent solutions that replace manual processes. You will own the solution lifecycle from discovery to iteration, bridging agentic architectures with high-impact business outcomes.

Responsibilities include designing multi-agent systems, integrating with SharePoint/Jira/SAP, and managing cloud deployments with CI/CD, while implementing guardrails and observability

Qualifications

• Experience building production-grade software solutions.
• Production projects delivering LLM agents, skill-building architectures, or RAG pipelines.
• Ability to own projects end-to-end with minimal guidance.
• Strong client-facing communication and ability to gather requirements.

Responsibilities

• Client embedding & workflow discovery with business stakeholders.
• Agentic AI engineering: design, build and deploy multi-agent systems.

Skills

Python mastery

API design

SQL & data processing

Production LLM experience

End-to-end ownership

Client-facing communication

DevOps & CI/CD

AWS cloud

Tools

Strands

LangGraph

CrewAI

AutoGen

Pinecone

pgvector

OpenSearch

Docker

GitHub Actions

AWS AgentCore

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.