About the Role

We are seeking an AI Developer to join our team and take ownership of our AI-powered solutions. You’ll be responsible for maintaining and enhancing existing AI systems, participating in requirement gathering sessions for new AI initiatives, and implementing cost-effective solutions using state-of-the-art language models and AI technologies. This role requires both technical expertise and the ability to translate business requirements into scalable AI solutions.

Requirements

Experience

3+ years of professional experience in AI/ML development or software engineering with significant AI focus

AI & Machine Learning Skills

Strong understanding of Large Language Models (LLMs), particularly closed-source models (OpenAI GPT-4, Anthropic Claude, Google Gemini)
Experience with prompt engineering and optimizing LLM interactions for cost and performance
Hands-on experience with Retrieval-Augmented Generation (RAG) architectures and implementation
Proficiency with vector databases (Pinecone, Weaviate, Qdrant, ChromaDB, pgvector)
Knowledge of embedding models and semantic search techniques
Experience with AI agent frameworks and automation tools (Browser Use, LangChain, AutoGPT, or similar)
Understanding of token optimization, caching strategies, and cost management for LLM APIs
Familiarity with fine-tuning and model evaluation techniques

Technical Skills

Strong proficiency in Python with experience in AI/ML libraries (LangChain, LlamaIndex, Hugging Face, OpenAI SDK, Anthropic SDK)
Experience with PostgreSQL and pgvector for vector search capabilities
Hands-on experience with MongoDB for document storage
Knowledge of Supabase for backend infrastructure and vector search
Experience with RabbitMQ for asynchronous task processing and message queuing
Proficiency with Docker for containerization and deployment
Hands-on experience with AWS services including:
– EC2 for compute resources
– S3 for data and model storage
– Lambda for serverless AI functions
– SageMaker, Bedrock, or similar AI services (nice to have)
Version control with Git and collaborative development workflows

Core Competencies

Ability to analyze and understand existing AI codebases and architectures
Strong problem-solving skills with focus on cost-optimization and performance
Experience participating in requirements gathering and translating business needs into technical solutions
Understanding of AI ethics, security, and data privacy considerations
Ability to evaluate trade-offs between different LLM providers and models
Knowledge of monitoring, logging, and debugging AI systems in production
Strong communication skills for explaining AI capabilities and limitations to stakeholders

Responsibilities

Maintain and enhance existing AI solutions, ensuring reliability and performance
Participate in meetings with stakeholders to gather requirements for new AI initiatives
Design and implement cost-effective AI solutions using appropriate LLMs and architectures
Build and optimize RAG pipelines for knowledge retrieval and context-aware responses
Implement and manage vector databases for semantic search and similarity matching
Develop AI agents and automation workflows using tools like Browser Use or similar frameworks
Monitor and optimize LLM API costs through effective prompt engineering and caching strategies
Integrate AI capabilities with existing Python backend services and databases
Deploy and manage AI services using Docker containers on AWS infrastructure
Implement asynchronous processing for AI tasks using RabbitMQ
Write comprehensive documentation for AI systems and integration patterns
Stay updated on latest LLM developments, pricing changes, and emerging AI technologies
Evaluate new AI tools, models, and services for potential adoption
Collaborate with cross-functional teams to identify AI opportunities and solutions
Ensure proper error handling, fallback mechanisms, and monitoring for AI services

Infrastructure Requirements

Since this is a completely work-from-home position, you will also require the following –

High-speed internet connectivity for video calls and efficient work.
Capable business-grade computer (e.g., modern processor, 8GB + of RAM, and no other obstacles to interrupted, efficient work).
Headphones with clear audio quality
Stable power connection and backups in case of internet/power failure.

Nice to Have

Experience with multiple LLM providers and model comparison/evaluation
Knowledge of streaming responses and real-time AI interactions
Familiarity with AI observability tools (LangSmith, Weights & Biases, Helicone)
Experience with function calling and tool use in LLMs
Understanding of context window management and chunking strategies
Knowledge of hybrid search (combining vector and keyword search)
Experience with CI/CD pipelines for ML/AI deployments
Familiarity with data annotation and dataset preparation
Understanding of model benchmarking and evaluation metrics
Experience with multimodal AI (vision, audio, text)
AWS AI/ML certifications
Contribution to AI/ML open-source projects
Experience with Agile/Scrum methodologies

AI Developer