We have a critical FDE opening for Bangalore. We are looking for candidates with experience in Agentic AI, LLM API integration, Prompt engineering, RAG pipelines with excellent communication skills.
Experience can be anywhere between 6 – 13 years overall. Please ensure the profiles are screened thoroughly before sharing.
Responsibilities
Agentic AI
• LLM API fundamentals — LLM API integration — tool use, function calling, streaming, context management
• Skill building — Design and publish reusable skills consumable by LLM-powered agent workflows
• MCP (Model Context Protocol) — Build and consume MCP servers; expose and integrate tools for agent use
• A2A communication — Multi-agent coordination, task delegation, result aggregation across agent networks
• RAG pipelines — Vector databases, chunking, embeddings, retrieval pipelines
• Prompt engineering — System prompts, chain-of-thought, evaluation and iteration
• Agent frameworks — Strands as primary framework; awareness of LangGraph, CrewAI, or AutoGen
• Guardrails — Hallucination mitigation, human-in-the-loop checkpoints, agent observability
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)
• REST API design, JWT / OAuth2
Workflow Automation
• Decompose manual business processes into agent pipelines
• Document processing — PDF, Excel, unstructured data extraction and classification
• Enterprise system integration — SharePoint, email, Jira, SAP or similar
Infrastructure
• AWS AgentCore — Host and operate agent workloads; understand lifecycle, scaling, and invocation patterns
• AWS services — EC2/ECS, Lambda, RDS, S3 — support agent deployment and data storage needs
• Docker and containerisation
• GitHub Actions CI/CD
ADDITIONAL SKILLS
• Next.js 15+, TypeScript, Tailwind CSS
• Terraform / Infrastructure as Code
• Kubernetes
• RPA tools — UiPath, Power Automate
• Fine-tuning and model evaluation
• CRE domain knowledge
EXPERIENCE
• Proven experience in software engineering
• At least one production project involving LLM agents, skill building, or RAG pipelines
• 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 advantag
Salary : As per industry standard.
Industry :IT-Software / Software Services
Functional Area : IT Software - Application Programming , Maintenance
We are seeking a hands-on DevOps Engineer with 4–6 years of experience in cloud infrastructure, CI/CD automation, and DevSecOps practices.
Key Skills & Responsibilities:
Strong experience in Azure Cloud and Azure Kubernetes Service (AKS).
Hands-on expertise with GitHub, Azure DevOps, and CI/CD pipeline implementation.
Proficient in Terraform for Infrastructure as Code (IaC).
Experience with SonarQube, Black Duck, Snyk, and security/vulnerability management.
Good understanding of Azure Networking, including VNets, NSGs, Private Endpoints, Private DNS, and Load Balancers.
Experience with Managed Identities, Service Principals, RBAC, and Azure Entra ID.
Knowledge of Docker, Kubernetes, Helm, and containerized deployments.
Strong scripting skills in PowerShell, Bash, or Python.
Experience with monitoring and logging tools such as Azure Monitor, Prometheus, Grafana, Application Insights, and Log Analytics.
Familiarity with Key Vault, APIM, Storage Accounts, and cloud security best practices.
Ability to troubleshoot production issues and support highly available cloud platforms.
Strong communication, collaboration, and problem-solving skills.
Required Qualifications:
Bachelor’s or master’s degree in computer science, Information Technology, or a related field.
Minimum of 3+ years’ experience and 3+ as DevOps Engineer
Excellent problem-solving skills and attention to detail.
Ability to work collaboratively in a team-oriented environment.
Preferred Skills:
Experience with Agile methodologies and DevOps practices.
Certifications: AZ-104, AZ-400, AZ-305 or equivalent Azure certifications.
Responsibilities
We are seeking a hands-on DevOps Engineer with 4–6 years of experience in cloud infrastructure, CI/CD automation, and DevSecOps practices.
Key Skills & Responsibilities:
Strong experience in Azure Cloud and Azure Kubernetes Service (AKS).
Hands-on expertise with GitHub, Azure DevOps, and CI/CD pipeline implementation.
Proficient in Terraform for Infrastructure as Code (IaC).
Experience with SonarQube, Black Duck, Snyk, and security/vulnerability management.
Good understanding of Azure Networking, including VNets, NSGs, Private Endpoints, Private DNS, and Load Balancers.
Experience with Managed Identities, Service Principals, RBAC, and Azure Entra ID.
Knowledge of Docker, Kubernetes, Helm, and containerized deployments.
Strong scripting skills in PowerShell, Bash, or Python.
Experience with monitoring and logging tools such as Azure Monitor, Prometheus, Grafana, Application Insights, and Log Analytics.
Familiarity with Key Vault, APIM, Storage Accounts, and cloud security best practices.
Ability to troubleshoot production issues and support highly available cloud platforms.
Strong communication, collaboration, and problem-solving skills.
Required Qualifications:
Bachelor’s or master’s degree in computer science, Information Technology, or a related field.
Minimum of 3+ years’ experience and 3+ as DevOps Engineer
Excellent problem-solving skills and attention to detail.
Ability to work collaboratively in a team-oriented environment.
Preferred Skills:
Experience with Agile methodologies and DevOps practices.
Certifications: AZ-104, AZ-400, AZ-305 or equivalent Azure certifications.
Salary : As per industry standard.
Industry :IT-Software / Software Services
Functional Area : IT Software - Application Programming , Maintenance
As discussed, sharing data engineering requirement for Bangalore location. Kindly share relevant profiles.
Must Have skillsets – Azure databricks, Data factory, Python, Pyspark, SQL
Experience – 5 to 8 years
Responsibilities
Salary : As per industry standard.
Industry :IT-Software / Software Services
Functional Area : IT Software - Application Programming , Maintenance
About the Role
JLL's Portfolio Services Technology function is building Navigator, a next-generation AI-powered platform that enables clients and JLL teams to model complex real estate portfolio scenarios, evaluate strategic options and make data-driven decisions at scale. Central to Navigator's intelligence layer is the ability to understand and reason about location — integrating geospatial data, demographic intelligence, labour market analytics and real estate market signals into the AI agents that power the platform.
We are looking for a Technical Product Lead — Data Scientist who combines deep data science capability with a product mindset and specialist expertise in location intelligence and geospatial AI. This is a hands-on senior role that sits at the intersection of data science, AI agent development and product strategy. You will build and own the models, pipelines and geospatial frameworks that underpin Navigator's analytical capabilities, while working directly with engineering, product and design teams to ensure those capabilities are embedded effectively into the platform.
This is not a pure research role. You will be responsible for production-grade outputs that directly inform client-facing AI recommendations — from site selection and labour force mapping to cost modelling and ESG scoring.
What You Will Do
Location Intelligence & Geospatial AI
• Design and build geospatial models that power Navigator's location scoring, market positioning and demographic analysis capabilities, integrating data from CoStar, labour market sources and third-party geospatial providers
• Develop location-based AI agent capabilities, including the Analytics Agent's real-time market intelligence layer, enabling the platform to surface relevant location insights for any given portfolio scenario
• Build and maintain geospatial data pipelines that ingest, transform and serve location data at the scale required for multi-portfolio analysis — including property-level data, demographic overlays, transport networks and ESG indicators
• Integrate map functionality into the Navigator platform, including synchronised list and map views, property clustering, search and filtering, and data overlays — working closely with engineering to ensure performance and usability
• Evaluate and onboard geospatial data sources, including CoStar and other third-party providers, assessing data quality, coverage and commercial terms for inclusion in the platform
AI Agent Development & Data Science
• Design, train and validate machine learning models that underpin Navigator's multi-criteria scoring framework — including Cost Optimisation, ESG/Sustainability, Talent Accessibility, Market Positioning and Risk Mitigation axes
• Own the data science architecture for the AI Scenario Agent, developing the model logic that generates and evaluates alternate portfolio strategies based on client-defined criteria and weighted priorities
• Build RAG pipelines and document intelligence capabilities that enable agents to reason over lease documents, market reports and financial data — directly relevant to the Lease Admin Agents programme
• Define evaluation frameworks and guardrails for AI output quality, including bias detection, accuracy validation and responsible AI compliance — ensuring model outputs are commercially credible and production-ready
• Monitor and optimise model performance in production, using NPS data from Pendo and user feedback from Optimal Workshop to identify where model outputs are falling short and iterating accordingly
Product Strategy & Stakeholder Collaboration
• Act as the data science product authority, translating business requirements from deep dive workshops and SME sessions into data science specifications that engineering teams can build against
• Own the analytical product roadmap, defining how location intelligence, geospatial AI and data science capabilities will evolve across Navigator's development phases — from current MVP through to future iterations
• Contribute to the AWS platform selection decision, specifically assessing the geospatial and ML infrastructure capabilities of AWS AgentCore and related services against Navigator's analytical requirements
• Participate in Critical Design Reviews (CDR), providing data science and geospatial expertise to ensure architectural decisions support the analytical capabilities the product requires
• Present model outputs, methodology and validation findings to senior stakeholders and client-facing audiences in clear, non-technical language
Governance & Standards
• Maintain documentation on model methodology, data sources, validation outcomes and geospatial data lineage in Confluence — supporting CDR compliance and responsible AI governance
• Ensure all geospatial and AI models comply with JLL's data governance policies, applicable data privacy regulations, and the AI Terms Addendum obligations under vendor contracts
• Support token cost management and optimisation across AI agent interactions, working with engineering to ensure the analytical layer operates efficiently at scale
What We Are Looking For
Essential
• 10+ years of hands-on data science experience, with at least 2 years working with geospatial data, location intelligence or spatial analytics in a product or platform environment
• Strong Python proficiency, including geospatial libraries such as GeoPandas, Shapely, Folium, PostGIS or equivalent
• Demonstrated experience building and deploying AI agents or LLM-based systems in production, including RAG design, agent orchestration and output evaluation
• Experience designing multi-criteria scoring and weighting frameworks for complex decision support applications
• Proficiency building and managing data pipelines on cloud infrastructure, ideally AWS or Azure
• Experience working with commercial real estate, demographic or labour market data sources — including CoStar, CBRE, or equivalent
• Strong product mindset — able to translate data science outputs into user-facing value and communicate model behaviour to non-technical stakeholders clearly
• Ability to operate across the full delivery cycle — from requirements and architecture through to production validation and iteration
Desirable
• Experience with AWS geospatial services, SageMaker or AWS AgentCore for production ML deployment
• Familiarity with ESG data frameworks, carbon emissions modelling or sustainability scoring methodologies
• Experience in real estate, financial services or enterprise SaaS environments
• Knowledge of vector databases, embeddings and semantic search for geospatial or document intelligence use cases
• Experience with Pendo, Optimal Workshop or equivalent product analytics and user research tools
• Familiarity with map rendering libraries and spatial visualisation tools for web applications
• Knowledge of responsible AI frameworks, bias evaluation and model governance for enterprise deployment
Key Technologies
Data Science
Geospatial
AI & Agents
Platform
Python · Pandas · NumPy · Scikit-learn · SQL (Postgres / SQLite)
GeoPandas · Shapely · PostGIS · Folium · CoStar API
LangChain / LlamaIndex · RAG · Vector DBs · AWS AgentCore · Claude / OpenAI
AWS / Azure · Confluence · Jira · Pendo · Optimal Workshop
Why This Role
Location intelligence is the foundation of every meaningful portfolio decision — and no one in the real estate industry is yet using it at the level Navigator is designed to operate. This role places you at the leading edge of how geospatial AI, location data and multi-agent systems come together in a production platform used by JLL's largest clients. You will not be running experiments — you will be building the analytical engine that powers decisions worth billions in real estate value. If you have the technical depth, the product instinct and the geospatial expertise, this is the role that lets you put all three to work.
About JLL
Jones Lang LaSalle (JLL) is a leading professional services firm specializing in real estate and investment management. Operating across more than 80 countries, JLL is committed to delivering technology-led solutions that create long-term value for clients, employees and communities
Responsibilities
Salary : As per industry standard.
Industry :IT-Software / Software Services
Functional Area : IT Software - Application Programming , Maintenance
