JLL supports the Whole You, personally and professionally.

Our people at JLL are shaping the future of real estate for a better world by combining world class services, advisory and technology to our clients. We are committed to hiring the best, most talented people in our industry; and we support them through professional growth, flexibility, and personalized perks to manage life in and outside of work. Whether you’ve got deep experience in commercial real estate, skilled trades, and technology, or you’re looking to apply your relevant experience to a recent industry, we empower you to shape a brighter way forward so you can thrive professionally and personally.

Senior Software Engineer - AI Engineering
Bengaluru

Role Summary
Embeds with client teams, understands manual business workflows, and builds AI-agent-powered automation to replace them. Helps build a new agent harness platform from the ground up — to be built on Claude (Claude Code /
Cowork), AWS Step Functions (ASL) and Amazon Bedrock AgentCore, with an AG-UI front end — and then delivers production workflows on it. Owns the solution end-to-end — discovery, build, deploy, evaluate, iterate — working
directly with enterprise customers with minimal direction.

TECHNICAL REQUIREMENTS

Harness Engineering — Core

- Harness engineering — Excellent understanding of designing agent harnesses: the control loop, tool and skill surface,

context and state management, and human-in-the-loop checkpoints around an LLM

- AWS Step Functions with ASL — Author Amazon States Language state machines to orchestrate agent steps,

branching, retries, parallelism and human-approval gates (e.g. task-token waits); invoke AgentCore runtimes and Lambda
from workflows

- Deterministic vs LLM control — Design workflows where policy gates and rules decide routing and the LLM only

proposes, with explicit exception, timeout and loop-guard paths

- Amazon Bedrock AgentCore — Host, operate and scale agent workloads on AgentCore Runtime; understand lifecycle,

scaling and invocation patterns, and expose tools via AgentCore Gateway

- AgentCore Observability — Hands-on tracing, metrics and logging of agent runs (AgentCore, CloudWatch, Datadog)

with a per-step audit trail to debug and monitor production workflows

- AgentCore Evaluation — Hands-on design and running of evaluations (AgentCore Evaluations, golden-dataset

regression tests) to measure agent quality before and after each release

- Guardrails — Hands-on configuration of Amazon Bedrock Guardrails and policy controls for safety, prompt-injection

defence,



PII and hallucination mitigation, with human-in-the-loop review where required

Agentic AI with Claude

- Claude Code / Cowork — Experience designing, deploying and scaling AI-powered production workflows using Claude

Code and/or Cowork

- LLM API fundamentals — Tool use, function calling, streaming and context management
- Skill building — Design and publish reusable skills consumable by agent workflows
- MCP (Model Context Protocol) — Build, host and consume MCP servers (e.g. FastMCP on AgentCore); expose and

integrate tools for agent use, with agents reaching data only through MCP/API, never directly

- Multi-agent coordination — Task delegation and result aggregation across agents (A2A)
- RAG pipelines — Vector databases, chunking, embeddings and retrieval
- Prompt engineering — System prompts, evaluation and iteration

Front End

- AG-UI — Build agent-facing user interfaces on the AG-UI protocol, connecting the front end to running agents for

streaming responses, tool-call visibility, shared state and human approval steps

Backend

- Python 3.10+ — async/await, type hints
- FastAPI or equivalent Python web framework
- Basic SQL — query, filter, join; awareness of vector DBs (pgvector, Pinecone, OpenSearch)
- NoSQL — Working knowledge of document/key-value stores (e.g. Amazon DynamoDB): data modelling, access

patterns, and using them for agent run state and audit trails

- REST API design, JWT / OAuth2

Workflow Automation

- Decompose manual business processes into agent workflows
- Document processing — PDF, Excel, unstructured data extraction and classification

AI Engineer
October 2026 JLL Confidential

- OCR — Extract text, tables and layout from scanned and image-based documents (e.g. AWS Textract), and feed the

output into agent workflows

- Enterprise system integration — SharePoint, email, and external systems via APIs and MCP

Infrastructure

- AWS services — Lambda, ECS, RDS, S3, IAM — support agent deployment and data storage needs
- Terraform / Infrastructure as Code — Provision and promote AgentCore, Step Functions, Lambda and supporting AWS

resources across environments

- Docker and containerisation
- GitHub Actions CI/CD





ADDITIONAL SKILLS

- Kubernetes
- TypeScript
- Fine-tuning and model evaluation
- CRE domain knowledge

EXPERIENCE

- Proven experience in software engineering, with hands-on AI engineering shipped to production (years of experience are

not the criterion; depth of AI delivery is)

- At least one production project involving LLM agents, skill building, or RAG pipelines — ideally on AWS Bedrock

AgentCore and/or Step Functions

- Direct experience working with enterprise customers to design, deploy and scale AI-powered production workflows using

Claude Code / Cowork

- Track record of owning and delivering solutions end-to-end with minimal guidance
- Experience working directly with non-technical stakeholders — gathering requirements, presenting solutions
- Consulting or client-facing background is an advantage

If this job description resonates with you, we encourage you to apply even if you don’t meet all of the requirements below. We’re interested in getting to know you and what you bring to the table!

Personalized benefits that support personal well-being and growth:

JLL recognizes the impact that the workplace can have on your wellness, so we offer a supportive culture and comprehensive benefits package that prioritizes mental, physical and emotional health.

About JLL –

We’re JLL—a leading professional services and investment management firm specializing in real estate. We have operations in over 80 countries and a workforce of over 102,000 individuals around the world who help real estate owners, occupiers and investors achieve their business ambitions. As a global Fortune 500 company, we also have an inherent responsibility to drive sustainability and corporate social responsibility. That’s why we’re committed to our purpose to shape the future of real estate for a better world. We’re using the most advanced technology to create rewarding opportunities, amazing spaces and sustainable real estate solutions for our clients, our people, and our communities.

Our core values of teamwork, ethics and excellence are also fundamental to everything we do and we’re honored to be recognized with awards for our success by organizations both globally and locally.

Creating a diverse and inclusive culture where we all feel welcomed, valued and empowered to achieve our full potential is important to who we are today and where we’re headed in the future. And we know that unique backgrounds, experiences and perspectives help us think bigger, spark innovation and succeed together.

📌 Senior Software Engineer (Bengaluru)
🏢 JLL
📍 Bengaluru