AI Native Developer in Sri Lanka for Claude-First Products
Senior consultant to design, build, and harden AI-native apps with Claude + modern tooling—ready for production.
Book a consultIf you’re searching for an AI Native Developer in Sri Lanka, you likely need more than “LLM integration.” You need someone who can shape the product, pick the right patterns, and deliver a reliable system that performs under real users, real data, and real constraints. I’m a senior AI-native consultant focused on building Claude-powered applications—chat and copilots, agentic workflows, internal tools, and customer-facing experiences—where AI is a core capability, not an add-on.
My approach is end-to-end: discovery and solution architecture, rapid prototyping, and production engineering. I work with Claude for high-quality reasoning and safe outputs, and I’m comfortable across the modern stack: RAG with vector databases, tool/function calling, structured outputs, prompt and policy design, evaluation harnesses, and observability. I build with practical guardrails—PII handling, access control, rate limiting, and failure-mode design—so your AI features remain dependable and auditable.
Delivery is engineering-led and measurable. You’ll get clear milestones, documented decisions, and working increments you can test with stakeholders. I can plug into your team as a hands-on consultant—pairing with engineers, reviewing PRs, and setting up best practices—or lead the build for a defined scope. Typical engagements include Claude integration, agent frameworks, RAG pipelines over your knowledge base, automation of support/sales ops, and AI-enriched dashboards.
Based in Sri Lanka and experienced with global teams, I prioritize crisp communication, predictable execution, and production readiness. If you want an AI-native system that’s accurate, secure, and maintainable—built around Claude and the best AI tools—let’s map your use case and ship something your users trust.
What you get with an AI-native senior consultant
Claude-first architecture & agent design
Designs agentic workflows, tool use, and structured outputs that align with Claude’s strengths while keeping behavior controllable and testable.
RAG done properly (not just a vector DB)
Creates retrieval pipelines with chunking strategy, hybrid search, reranking, citations, and freshness controls to reduce hallucinations.
Production guardrails, security & compliance
Implements PII redaction, permission-aware retrieval, audit logs, prompt/policy separation, and safe fallback paths for high-stakes flows.
Evaluation, observability & cost control
Sets up offline evals, golden datasets, telemetry, and token/caching strategies so quality and spend improve over time.
“We went from a messy prototype to a Claude-powered assistant our support team actually trusts. The architecture, evals, and guardrails made the difference.”
Frequently asked questions
- What does “AI-native development” mean in practice?
- It means the product is designed around AI capabilities from day one: workflows, data access, and UI/UX assume an LLM is a core component. You get robust prompting/policies, tool calling, retrieval, and evaluation built into the engineering process—not bolted on after the fact.
- Can you work specifically with Claude and Anthropic tooling?
- Yes. I build Claude-first systems including prompt/policy design, tool/function calling, structured outputs, and safety-focused behaviors. If your stack also uses other models or providers, I can design an abstraction layer so you can swap models without rewriting the product.
- How do you reduce hallucinations and make answers verifiable?
- I use retrieval with citations, reranking, and permission-aware context, plus constraints like JSON schemas and “answer from sources only” policies where needed. I also set up evaluation suites and monitoring so regressions are caught before users notice.
- What engagement models do you offer and what do you need to start?
- I offer fixed-scope builds for defined MVPs and retainer-style consulting for ongoing iteration with your team. To start, we’ll align on the use case, data sources, risk profile, success metrics, and access requirements—then I’ll propose a plan with milestones and deliverables.