Own the full lifecycle of GenAI-powered products from model and RAG integration to production-grade full stack delivery.

Experience Mid-level 3-5 years

Function Engineering AI / Full Stack

Employment Full-time On-site / Hybrid

We're building GenAI-powered applications that combine large language models, retrieval systems, and cloud-native infrastructure. We're looking for an engineer who can own the full lifecycle from model and RAG integration through to production-grade full-stack development and ship independently with minimal oversight.

What You'll Do

Design and build end-to-end architecture for AI powered applications, from UI through backend to cloud infrastructure.

Develop RAG pipelines, integrate LLMs, and build MCP based agentic workflows.

Build responsive, production-quality front-end interfaces using React.

Develop and maintain backend services and APIs using Node.js and Python.

Deploy, scale, and monitor AI workloads on AWS. Evaluate and monitor LLM/RAG output quality in production.

Partner closely with product, design, and QA to translate requirements into shipped features.

Troubleshoot independently and propose solutions not just surface problems.

Must-Have Skills

CORE EXPERIENCE

3-5 years in software / full-stack development.

Proficiency in Python.

FULL STACK DEVELOPMENT

Proficiency in React, JavaScript/TypeScript, HTML, and CSS.

Backend development with Node.js and RESTful API design.

SQL/NoSQL databases, Git, and version control (GitHub or Bitbucket).

AI & NLP

Strong NLP foundation: tokenization, preprocessing, POS tagging, NER, vectorization (BoW, TF-IDF, Word2Vec/embeddings).

Solid grasp of transformer architecture (self-attention, multi-head attention, positional encoding) and how LLMs are trained.

Hands-on experience building RAG systems, including hybrid search.

Prompt engineering designing, testing, and iterating on prompts for production.

Vector databases (FAISS, ChromaDB, or Pinecone).

Working knowledge of LangChain and MCP (Model Context Protocol).

CLOUD AWS / ATLASSIAN

Practical experience with core AWS services: Lambda, Bedrock, DynamoDB, and IAM.

Hands-on experience with the Atlassian platform (Jira / Confluence / JSM).

Experience integrating with Atlassian REST APIs and app development (Forge or Connect).

SOFT SKILLS

Excellent written and verbal communication skills.

Ability to work independently and drive problems to resolution.

Good to Have

LangGraph, CrewAI, AutoGen, or similar frameworks for stateful, multi-agent applications.

LLM/RAG evaluation and observability tooling (e.g., RAGAS, LangSmith).

Fine-tuning experience (LoRA/QLoRA, quantization) on open models such as Gemma.

Atlassian Forge platform (UI Kit / Custom UI, resolvers, manifest.yml, Forge Storage/SQL).

Jira / Confluence / JSM REST APIs and OAuth 2.0 app scopes.

SageMaker, EC2, Cognito, or S3.

Containerization and CI/CD (Docker, GitHub Actions, or equivalent).

API security rate limiting, input validation, prompt-injection mitigation for LLM-facing endpoints.

Unit testing experience (Jest or equivalent).

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

AI Full Stack Engineer

Job Description

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