Mandatory Skills Python, Agentic AI, LLM API, VECTOR Database

About the Role

We are seeking an experienced AI Agent Engineer to join our team and drive the transformation of manual business workflows into intelligent, AI-powered automation solutions. In this role, you will embed with client teams, deeply understand their operational challenges, and architect end-to-end agentic AI solutions that deliver measurable impact.

You will own the complete project lifecycle from discovery and design through build, deployment, and iterative refinement working directly with clients and internal stakeholders with minimal direction. This is an ideal opportunity for a self-motivated engineer who thrives in dynamic environments and is passionate about leveraging cutting-edge AI technology to solve real-world business problems.

Key Responsibilities

- Client Engagement & Discovery: Embed with client teams to understand manual workflows, identify automation opportunities, and translate business requirements into technical specifications.
- Solution Architecture: Design and architect agentic AI solutions that decompose complex business processes into scalable agent pipelines and workflows.
- Development & Implementation: Build production-grade AI agents using contemporary frameworks and LLM APIs, including tool integration, function calling, and context management.
- Skill & Capability Building: Design and publish reusable skills and tools consumable by LLM-powered agent workflows; implement Model Context Protocol (MCP) servers for seamless tool integration.
- RAG & Data Pipeline Development: Architect and implement retrieval-augmented generation (RAG) pipelines, including vector database integration, chunking strategies, and retrieval optimization.
- Enterprise Integration: Integrate AI agents with enterprise systems including SharePoint, email, Jira, SAP, and other business-critical platforms.
- Deployment & Operations: Deploy and operate agent workloads on AWS infrastructure; manage scaling, monitoring, and lifecycle operations.
- Quality & Safety: Implement guardrails, hallucination mitigation strategies, and human-in-the-loop checkpoints to ensure reliable and trustworthy agent behavior.
- Iteration & Optimization: Continuously evaluate, test, and refine solutions based on client feedback and performance metrics.

Required Skills & ExperienceAgentic AI & LLM Expertise
- Strong understanding of LLM API fundamentals, including tool use, function calling, streaming, and context management.




- Hands-on experience designing and implementing reusable skills for LLM-powered agent workflows.
- Proficiency with Model Context Protocol (MCP) building and consuming MCP servers, exposing tools for agent use.
- Experience with multi-agent coordination, task delegation, and result aggregation across agent networks.
- Proven expertise in RAG pipeline development, including vector databases, chunking strategies, and retrieval optimization.
- Strong prompt engineering skills, including system prompts, chain-of-thought reasoning, and prompt evaluation.
- Hands-on experience with agent frameworks, particularly Strands ; familiarity with LangGraph, CrewAI, or AutoGen is advantageous.
- Knowledge of guardrails implementation, hallucination mitigation, and agent observability.

Backend & Software Engineering
- Proficiency in Python 3.10+ , including async/await patterns and type hints.
- Experience with FastAPI or equivalent Python web frameworks.
- Solid understanding of SQL fundamentals queries, filtering, joins; awareness of vector databases (pgvector, Pinecone, OpenSearch).
- Expertise in REST API design, authentication protocols (JWT, OAuth2), and API security.
- At least one production project involving LLM agents, skill building, or RAG pipelines.

Workflow Automation & Integration
- Ability to decompose manual business processes into intelligent agent pipelines.
- Experience with document processing PDF, Excel, unstructured data extraction, and classification.
- Familiarity with enterprise system integration (SharePoint, email, Jira, SAP, or similar platforms).

Infrastructure & DevOps
- Hands-on experience with AWS AgentCore for hosting and operating agent workloads; understanding of lifecycle, scaling, and invocation patterns.
- Proficiency with AWS services including EC2/ECS, Lambda, RDS, and S3.
- Experience with Docker and containerization.
- Familiarity with GitHub Actions for CI/CD pipelines.

Professional Experience
- Track record of owning and delivering end-to-end solutions with minimal guidance.
- Proven ability to work directly with non-technical stakeholders gathering requirements, presenting solutions,



and managing expectations.
- Consulting or client-facing background is a significant advantage.

Preferred Skills & Experience
- Frontend development with Next.js 15+ , TypeScript, and Tailwind CSS.
- Infrastructure as Code expertise with Terraform.
- Kubernetes orchestration and management.
- RPA tools experience (UiPath, Power Automate).
- LLM fine-tuning and model evaluation.
- Domain knowledge in Commercial Real Estate (CRE) or related industries.

What Were Looking For
- A self-motivated engineer who thrives with autonomy and takes ownership of solutions end-to-end.
- Strong problem-solving skills with the ability to translate complex business challenges into technical solutions.
- Excellent communication skills and the ability to collaborate effectively with both technical and non-technical teams.
- A passion for AI and automation, with a commitment to staying current with emerging technologies and best practices.
- Attention to detail, quality assurance mindset, and a focus on delivering reliable, production-grade solutions.

Why Join Us
- Work at the forefront of AI innovation, building intelligent automation solutions that transform how businesses operate.
- Enjoy significant autonomy and ownership youll drive projects from conception to production with minimal oversight.
- Collaborate with diverse teams and clients, expanding your technical expertise and business acumen.
- Access to cutting-edge tools, frameworks, and cloud infrastructure to support your development.
- Continuous learning opportunities in a rapidly evolving field with exposure to emerging AI technologies and methodologies.

Qualifications Summary

Minimum Requirements:

- At least one production project involving LLM agents, skill building, or RAG pipelines.
- Proficiency in Python 3.10+ and FastAPI or equivalent framework.
- Hands-on experience with LLM APIs and agent frameworks (Strands preferred).
- Strong understanding of AWS services and containerization (Docker).
- Proven ability to deliver end-to-end solutions with minimal guidance.
- Experience working directly with non-technical stakeholders.

Preferred Qualifications:

- Multiple production projects involving agentic AI or advanced RAG implementations.
- Consulting or client-facing background.
- Full-stack development capabilities (backend + frontend).
- Infrastructure as Code and Kubernetes expertise.
- Domain-specific knowledge in relevant industries.

Location & Work Environment

📌 Forward Deployed Engineer (Bengaluru)
🏢 Cephas Consultancy Services
📍 Bengaluru