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 siloyou 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: Robust 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.

📌 Forward Deployed Engineer (Bengaluru)
🏢 Ciklum
📍 Bengaluru