About the Role

Role Summary

AI Powered Tech Talent

Build high quality agentic AI applications—implement LLM tooling, RAG pipelines, vector search, and API integrations—delivering rapid prototypes that evolve into production systems. Own hands on development, testing, and integration, with a portfolio that demonstrates speed, experimentation, and learning.

Responsibilities

Hands on Build: Implement agents (tools, skills), prompts/templates, planners, memory, and evaluation loops write clean, testable code and CI/CD pipelines.
Integration: Connect to enterprise APIs, event streams, and data sources ensure robust error handling, retries, and fallbacks.
Quality & Safety: Write unit/integration tests implement offline/online evals, red team scenarios, and content/action safety boundaries.
Iteration & Communication: Prototype quickly, demo frequently, and communicate trade offs and results clearly with stakeholders.

Must Have Qualifications (AI Native Archetype)

Strong CS and software engineering fundamentals.
Hands on experience with LLMs, RAG, vector DBs, and AI APIs.
Proven ability to build end to end applications and integrate AI into systems.
Visible portfolio of AI projects demonstrating experimentation and speed.
Fast learner with a bias for rapid prototyping and iteration.
Able to translate business problems into practical AI solutions with clear communication.

Programming Languages (Developer)

Core build proficiency (choose two or more):

Python (agent frameworks, data/RAG services, evaluation, notebooks to services)
TypeScript/Node.js (service wrappers, tool servers, API integration, front end hooks)
Java (enterprise services, Spring Boot, concurrency/performance)

Nice to have

C#/.NET (enterprise stacks)
Go (high throughput agents/services)
Rust (performance critical tooling)
SQL (PostgreSQL/pgvector, query optimization)
Bash (DevOps)

Frameworks & tooling

LangChain, LlamaIndex, Semantic Kernel vector DBs (pgvector, Pinecone, Weaviate, Milvus) test frameworks (PyTest/JUnit/Jest) containers, serverless, and cloud SDKs.

Additional Information

The candidate should have minimum 7.5 years of experience in Java Full Stack Development. A 15 years full time education is required.

Requirements

Java Full Stack Development

Minimum 7.5 years of experience in Java Full Stack Development is required.

AI Application Development

Hands-on experience with LLMs, RAG, vector DBs, and AI APIs is essential.

Software Engineering Fundamentals

Strong computer science and software engineering fundamentals are necessary.

Prototyping Skills

Ability to rapidly prototype and iterate on AI solutions is crucial.

Nice to Have

Rust

Experience with Rust for performance-critical tooling is a plus.

C#/.NET

Familiarity with C#/.NET for enterprise stacks is beneficial.

Knowledge of Go for high throughput agents/services is advantageous.