Manager, Intelligent Automation
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Our people at JLL are shaping the future of real estate for a better world by combining world class services, advisory and technology for our clients. We are committed to hiring the best, most talented people and empowering them to thrive, grow meaningful careers and to find a place where they belong. Whether you’ve got deep experience in commercial real estate, skilled trades or technology, or you’re looking to apply your relevant experience to a new industry, join our team as we help shape a brighter way forward.
About JLL
We’re JLL. We’re a professional services and investment management firm specializing in real estate. We help organizations around the world achieve their ambitions by owning, occupying and investing in real estate.
If you’re looking to step up your career, JLL is the perfect professional home. At JLL, you’ll have a chance to innovate with the world’s leading businesses, put that expertise into action on landmark projects, and work on game-changing real estate initiatives. You’ll also make long-lasting professional connections through sharing different perspectives, and you’ll be inspired by the best. We’re focused on opportunity and want to help you make the most of yours. Achieve your ambitions – join us at JLL!
Role Summary
We are looking for a senior automation engineer (4+ years) who can independently own the full lifecycle of business process automations — from requirements through deployment and support — and who is equally comfortable building traditional UDA solutions (Python/VBA-based attended and unattended automations) and next-generation Gen AI and agentic AI capabilities. This role combines expert-level Selenium/web automation and VBA/Excel competency for legacy system integration with hands-on experience applying large language models (LLMs) as production automation components. Critically, the role now extends beyond single-shot prompting into agentic AI: designing and building autonomous or semi-autonomous agents that can plan, use tools, reason across multiple steps, and orchestrate other agents to complete business workflows with minimal human intervention. This is a senior individual-contributor role for someone who can translate business problems into scalable technical solutions — spanning classic automation, applied Gen AI, and agentic systems — architect clean and maintainable code, and deliver production-ready outcomes without hand-holding.
Core Technical Requirements
Python Development
- Strong proficiency in Python 3.x with 4+ years hands-on experience
- Deep understanding of OOP principles, error handling, and code modularity
- Experience packaging Python applications into executables using PyInstaller, cx_Freeze, or auto-py-to-exe
- Knowledge of virtual environments and dependency management (pip, requirements.txt)
Selenium & Web Automation
- Expert-level Selenium WebDriver experience for browser automation
- Handling dynamic content, iframes, pop-ups, alerts, and AJAX calls
- Experience with explicit/implicit waits and element locators (XPath, CSS selectors)
- Knowledge of headless browser operations and handling CAPTCHAs
- Familiarity with additional tools: Beautiful Soup, Scrapy, Requests library
Data Processing & File Handling
- Excel manipulation: openpyxl, pandas, xlwings, xlrd/xlsxwriter
- PDF processing: PyPDF2, pdfplumber, tabula-py, camelot
- OCR implementation: Tesseract, pytesseract, EasyOCR, or cloud OCR APIs
- Data transformation and cleansing with pandas and numpy
VBA & Excel Macros
- Working knowledge of VBA for Excel automation; ability to read, modify, and maintain existing macros
- Experience with the Excel object model: Workbooks, Worksheets, Ranges, PivotTables
- Integration between Python and Excel macros using xlwings or win32com (pywin32)
- Sound judgment on when to use VBA vs. Python for a given automation task
- Knowledge of macro security, digital signatures, and programmatic macro enablement
- Experience with Excel events, user forms, and custom functions (UDFs)
Applied Gen AI & Prompt Engineering
- Expert-level prompt engineering for business automation use cases: data extraction, document classification, content generation, entity recognition, and decision/validation logic
- Prompt optimization techniques: few-shot learning, chain-of-thought prompting, role-based prompting, context management
- Understanding of hallucination handling and output-validation strategies for production use
- Ability to design prompts that reliably produce structured outputs (JSON, CSV)
- Knowledge of temperature, token limits, and parameter tuning
- Experience building reusable prompt templates with dynamic variable insertion
- Working experience with RESTful APIs — authentication, request/response handling, error management, rate limiting — including LLM provider APIs (OpenAI, Anthropic, Azure OpenAI)
Agentic AI Development
This is the newest and fastest-growing part of the role: moving beyond single-turn prompting to building autonomous and semi-autonomous agents that plan, act, and collaborate to complete multi-step business workflows.
- Agent frameworks: hands-on experience with at least one of LangChain, LangGraph, AutoGen, CrewAI, or Semantic Kernel
- Multi-agent orchestration: designing planner-executor, supervisor-worker, and reflection/critique patterns; coordinating specialist agents toward a shared goal
- Tool / function calling: defining and exposing tools (APIs, scripts, database calls) that an agent can invoke, and validating tool outputs before they drive downstream actions
- Model Context Protocol (MCP) or equivalent: connecting agents to enterprise systems and data sources through standardized tool/connector interfaces
- Retrieval-Augmented Generation (RAG): chunking and embedding strategies, vector databases (e.g., FAISS, Chroma, Pinecone, Azure AI Search), and retrieval quality tuning
- Agent memory & state management: short-term (conversation/task) and long-term memory design; session and workflow state persistence
- Guardrails & human-in-the-loop design: building approval checkpoints, escalation paths, and safety rails so agents fail safely and stay within defined authority
- Agent evaluation & observability: tracing and debugging agent runs (e.g., LangSmith, Langfuse), monitoring token cost, latency, and success/failure rates
- Autonomy calibration: judgment on when a workflow should be fully autonomous vs. human-supervised, and how to design for graceful degradation when the agent is uncertain
- Enterprise integration: connecting agentic workflows to business systems (ERP, ticketing/ITSM, SharePoint, email/chat) via APIs
- Cloud agent platforms (Preferred): hands-on experience with AWS Bedrock AgentCore (or an equivalent managed agent runtime/orchestration service) is a strong plus
Professional Competencies
Independent Work Capability
- Proven track record of owning the complete SDLC: requirements gathering, design, development, testing, deployment, and maintenance
- Self-starter who can translate business requirements into technical solutions with minimal supervision
- Documentation skills for code, prompts/agent designs, and user guides
Version Control & Collaboration
- Proficient with Git/GitHub: branching, merging, pull requests, conflict resolution
- Understanding of gitignore, commit best practices, and collaborative workflows
- Experience with code reviews and maintaining a clean repository structure
Code Quality & Best Practices
- Writing clean, maintainable, well-documented code following PEP 8
- Implementing logging, exception handling, and structured debugging
- Use of config files and environment variables for secrets and sensitive data
- Code reusability through functions, classes, and modules
Responsible AI & Governance Mindset NEW
- Awareness of data privacy, PII handling, and access-control implications when agents touch enterprise systems
- Comfort working within governance frameworks for AI/automation change control and audit trail requirements
- Ability to explain agent/prompt behavior in business terms to non-technical stakeholders
Preferred / Nice-to-Have
- Hands-on experience with AWS Bedrock AgentCore or another managed agentic automation platform
- Familiarity with low-code UDA tools such as Alteryx alongside Python/VBA
- Experience contributing to or maintaining an internal library of reusable agent/prompt components
- Prior experience in RPA-adjacent roles (UiPath, Automation Anywhere, Power Automate) is a plus, though this role is Python-first
Experience & Seniority Expectations
- Core automation experience: 4+ years hands-on with Python-based automation, Selenium, and VBA/Excel integration
- Applied Gen AI experience: demonstrable production or pilot use of LLM prompting for a business workflow (not just experimentation)
- Agentic AI experience: hands-on exposure to building at least one multi-step or multi-agent workflow (pilot, hackathon, or production) is required; deeper experience is a strong differentiator given the rapid growth of this area
- Seniority: senior individual contributor who needs minimal supervision and can mentor others on Gen AI / agentic techniques as the practice matures
Location:
On-site –Bengaluru, KA, Gurugram, HR, Hyderabad, TSScheduled Weekly Hours:
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JBSIf this job description resonates with you, we encourage you to apply, even if you don’t meet all the requirements. We’re interested in getting to know you and what you bring to the table!
At JLL, we harness the power of artificial intelligence (AI) to efficiently accelerate meaningful connections between candidates and opportunities. Using AI capabilities, we analyze your application for relevant skills, experiences, and qualifications to generate valuable insights about how your unique profile aligns with the specific requirements of the role you're pursuing.
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