1. Rapid Prototyping & Application Development
Build AI applications, copilots, and agentic workflows end-to-end – UI, APIs, business logic, and model integration.
Use rapid development tools (Cursor, Claude Code, Replit, Google AI Studio) to compress build cycles and iterate quickly with users and stakeholders.
Turn loosely-defined requirements into working demos and prototypes within days, then refine based on feedback.
2. Agentic & GenAI Engineering
Develop with agentic SDKs and frameworks – OpenAI Agents SDK, Anthropic Claude (Agent SDK / API), Google Gemini & ADK, LangChain/LangGraph.
Implement RAG pipelines, tool/function calling, structured outputs, and prompt engineering with systematic testing and evals.
Integrate models and agents with enterprise data sources and APIs, handling auth, rate limits, and error paths properly.
3. Engineering Quality & Productionization
Write clean, testable, well-documented code; use Git, containers, and CI/CD as standard practice.
Partner with Forward Deployment Engineers and platform teams to take successful prototypes into production, adding monitoring, guardrails, and cost controls.
Balance speed and quality pragmatically – knowing when to hack and when to harden.
4. Collaboration & Continuous Learning
Work closely with architects, data scientists, and designers; contribute to demos, accelerators, and internal hackathons.
Stay current with the fast-moving model and tooling landscape, and share learnings across the team.
Evangelize AI-assisted development practices that raise the whole team’s velocity.
Rapid development tools as daily drivers Cursor, Claude Code, Replit, Google AI Studio, GitHub Copilot – demonstrated ability to ship real software with AI-assisted workflows.
Agentic SDKs & frameworks hands-on experience with OpenAI Agents SDK, Anthropic Claude APIs/Agent SDK, Google Gemini/ADK, and LangChain or LangGraph.
Strong programming skills in Python and/or TypeScript/JavaScript; comfort building full-stack prototypes (React/Node) and REST APIs.
LLM application patterns prompt engineering, function/tool calling, structured outputs, RAG with vector stores (pgvector, Pinecone, FAISS, or similar).
Testing & observability basics writing evals, using tracing tools (LangSmith, Langfuse, or similar), and monitoring cost/latency/quality.
Engineering foundations Git, Docker, CI/CD, and at least one cloud (AWS/Azure/GCP).
Good to have voice/multimodal experience (ElevenLabs, HeyGen), MCP-based tool integration, fine-tuning or open-source LLM experience.
Speed of delivery consistent idea-to-prototype turnaround in days and prototype-to-production in weeks.
Volume and quality of shipped work applications, demos, and accelerators that are actually used by stakeholders and internal teams.
Reliability of what ships low defect rates, sensible test/eval coverage, and predictable cost/latency behavior.
Contribution to reuse components, patterns, and utilities adopted by other engineers.
Team velocity uplift through shared AI-assisted development practices.
4–8 years of software engineering experience, with 1–2+ years building GenAI/LLM applications hands-on.
A portfolio of shipped AI work – products, prototypes, GitHub projects, or demos you can walk us through.
Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent practical experience).
Demonstrated fluency with AI-native development tools (Cursor, Claude Code, Replit, AI Studio) in real projects – not just experimentation.
Strong problem-solving skills and product sense – you care about whether the thing you built actually gets used.
Clear written and verbal communication; comfortable demoing your work to technical and business audiences.
Choosing a digital partner is about more than capabilities — it’s about collaboration and character.
Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments.
At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations.
Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale.
Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact.
We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition.
At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward.
For more information, visit www.exlservice.com.
