Build and ship internal tools, backend services, APIs, frontend interfaces, data integrations, automation, and AI-powered features. Integrate LLM, RAG, and agent capabilities into usable software, collaborate with teams across the business, and own solutions through production. The role requires adaptable full-stack engineering, data fluency, AI integration experience, autonomy, and reliable end-to-end delivery.
About the team
We’re the company’s internal AI & Data team — a small, fast-moving pod. Our mission is to make the rest of the company dramatically more capable, using AI and Data to automate work, unlock insight, and build the tools and systems teams rely on.
This role is the versatile builder who turns all of that into working software — and who can pick up whatever the moment demands.
The roleYou’re a builder, full stop. You’ll work on many things — internal tools, services, interfaces, integrations, automation. You’ll move fluidly between them as priorities shift. This is deliberately a broad, flexible seat: we’re not hiring for one stack or one problem, we’re hiring someone who can build whatever the company needs next and do it well.
AI is a tool in your kit, not the thing you specialize in. You don’t need to design retrieval systems or agents from scratch — but you’re comfortable working with them, wiring them into products, and shipping the software around them. Your superpower is range and reliability: you take things from idea to shipped, across the stack, without needing a narrow lane.
What you’ll do
- Build across the stack. Design and ship internal tools and systems end to end — back-end services and APIs, front-end interfaces, data integrations, and the deployment and infrastructure glue that makes them real.
- Work on many things. Move between projects and problem types as priorities shift — one week a workflow-automation tool, the next an internal dashboard, the next helping ship an AI-powered feature. Breadth is the point.
- Put AI to work. Integrate the LLM, RAG, and agent capabilities the team builds into usable software, partnering closely with the Applied AI Engineer to turn intelligence into product.
- Enable the company. Sit with teams across the business, understand their problems, and build the right solution — measured by how much more effective you make everyone else.
- Ship reliably. Own what you build through to production and beyond, with the quality and judgment to know when good-enough-shipped beats perfect-delayed.
What you'll bring:
- Strong full-stack engineering. You write production-grade code and build comfortably across the stack — back end, APIs, and front end (e.g. Python and/or TypeScript with a modern web framework). You’re not boxed into one layer.
- Range and adaptability. A track record of picking up unfamiliar problems and shipping — you’re energized by variety, not thrown by it.
- Comfort with AI as a tool. You’ve worked extensively with AI — integrating APIs, building features on top of models — even if AI isn’t your specialty.
- A builder who talks to people. You can understand a non-technical team’s problem and turn it into a working solution. Internal enablement rewards engineers who listen as well as they build.
- Data fluency. Enough comfort with pipelines, databases, and structured/unstructured data to work directly with what your software touches.
- Autonomy in a small team. You thrive without heavy process, set your own direction, and are happy wearing whatever hat the moment calls for.
Bonus points
- Experience building internal tools or platforms that other teams depend on.
- Cloud, DevOps, or deployment experience — CI/CD, containers, infrastructure-as-code.
- Hands-on experience shipping LLM-powered features in production.
- A portfolio of varied systems you’ve built end to end.
Similar Jobs
Aerospace • Artificial Intelligence • Cloud • Machine Learning • Software • Cybersecurity • Defense
Develop advanced avionics features for Honeywell’s ANTHEM cockpit platform. Responsibilities include analyzing customer and operational requirements, defining system architecture, managing requirements, integrating and testing systems, troubleshooting interfaces, conducting design reviews, and supporting SRR, PDR, and CDR milestones. The role requires collaboration across global teams, avionics certification knowledge, Agile development experience, and strong systems engineering expertise.
Top Skills:
AgileArp4754AAtlassian JiraAvionics ArchitectureAvionics SoftwareAvionics SystemsDisplay SystemsEpic/ApexIbm Rational Doors NgSystems EngineeringSystems Safety Analysis
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Leads the architecture, development, and productionization of AI/ML and GenAI solutions for healthcare operations. Responsibilities include building clinical and claims data pipelines, developing LLM and RAG applications, implementing MLOps and LLMOps, ensuring HIPAA-compliant governance, translating business needs into technical roadmaps, communicating with stakeholders, and mentoring engineers.
Top Skills:
AirflowAWSAzureAzure MlBigQueryCi/CdDaskDatabricksDockerFaissGCPGitGoHugging FaceJavaKafkaKubernetesLangchainLlamaindexMlflowNeo4JNumpyPandasPgvectorPineconePrefectPytestPythonPyTorchSagemakerScalaSnowflakeSparkSQLTensorFlowTerraformTransformersVertex Ai
Cloud • Information Technology • Security • Software • Cybersecurity
As a Senior Business Systems Analyst, you will define system goals, capture business requirements, and work with engineering teams on SFDC implementations.
Top Skills:
Experience CloudSales CloudSalesforce
What you need to know about the Delhi Tech Scene
Delhi, India's capital city, is a place where tradition and progress co-exist. While Old Delhi is known for its rich history and bustling markets, New Delhi is defined by its modern architecture. It's clear the region places a strong emphasis on preserving its cultural heritage while embracing technological advancements, particularly in artificial intelligence, which plays a central role in shaping the city's tech landscape, fueled by investments in research and development.
