Forage AI Careers!
AI Developer
Technology
Full Time
Remote
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:
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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
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Hands-on experience with Retrieval-Augmented Generation (RAG) architectures and implementation
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Proficiency with vector databases (Pinecone, Weaviate, Qdrant, ChromaDB, pgvector)
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Knowledge of embedding models and semantic search techniques
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Experience with AI agent frameworks and automation tools (Browser Use, LangChain, AutoGPT, or similar)
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Understanding of token optimization, caching strategies, and cost management for LLM APIs
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Familiarity with fine-tuning and model evaluation techniques
Technical Skills:
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Strong proficiency in Python with experience in AI/ML libraries (LangChain, LlamaIndex, Hugging Face, OpenAI SDK, Anthropic SDK)
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Experience with PostgreSQL and pgvector for vector search capabilities
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Hands-on experience with MongoDB for document storage
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Knowledge of Supabase for backend infrastructure and vector search
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Experience with RabbitMQ for asynchronous task processing and message queuing
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Proficiency with Docker for containerization and deployment
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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:
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Ability to analyze and understand existing AI codebases and architectures
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Strong problem-solving skills with focus on cost-optimization and performance
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Experience participating in requirements gathering and translating business needs into technical solutions
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Understanding of AI ethics, security, and data privacy considerations
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Ability to evaluate trade-offs between different LLM providers and models
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Knowledge of monitoring, logging, and debugging AI systems in production
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Strong communication skills for explaining AI capabilities and limitations to stakeholders
Responsibilities
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Maintain and enhance existing AI solutions, ensuring reliability and performance
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Participate in meetings with stakeholders to gather requirements for new AI initiatives
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Design and implement cost-effective AI solutions using appropriate LLMs and architectures
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Build and optimize RAG pipelines for knowledge retrieval and context-aware responses
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Implement and manage vector databases for semantic search and similarity matching
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Develop AI agents and automation workflows using tools like Browser Use or similar frameworks
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Monitor and optimize LLM API costs through effective prompt engineering and caching strategies
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Integrate AI capabilities with existing Python backend services and databases
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Deploy and manage AI services using Docker containers on AWS infrastructure
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Implement asynchronous processing for AI tasks using RabbitMQ
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Write comprehensive documentation for AI systems and integration patterns
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Stay updated on latest LLM developments, pricing changes, and emerging AI technologies
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Evaluate new AI tools, models, and services for potential adoption
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Collaborate with cross-functional teams to identify AI opportunities and solutions
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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 –
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High-speed internet connectivity for video calls and efficient work.
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Capable business-grade computer (e.g., modern processor, 8GB + of RAM, and no other obstacles to interrupted, efficient work).
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Headphones with clear audio quality
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Stable power connection and backups in case of internet/power failure.
Nice to Have
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Experience with multiple LLM providers and model comparison/evaluation
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Knowledge of streaming responses and real-time AI interactions
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Familiarity with AI observability tools (LangSmith, Weights & Biases, Helicone)
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Experience with function calling and tool use in LLMs
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Understanding of context window management and chunking strategies
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Knowledge of hybrid search (combining vector and keyword search)
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Experience with CI/CD pipelines for ML/AI deployments
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Familiarity with data annotation and dataset preparation
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Understanding of model benchmarking and evaluation metrics
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Experience with multimodal AI (vision, audio, text)
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AWS AI/ML certifications
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Contribution to AI/ML open-source projects
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Experience with Agile/Scrum methodologies
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