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

- Robust 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

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Manager, Intelligent Automation (Hyderabad)
🏢 Jones Lang LaSalle (JLL)
📍 Hyderabad