Junior AI Engineer, Full Stack Developer

BIP Ventures

. Add AI capabilities, LLM-powered features, workflows, and interfaces to existing full-stack applications .

Posted 9/17/2026full-timeAtlanta • United StatesJuniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and improving LLM-powered features and workflows, with a strong foundation in software engineering principles, particularly in Node.js and TypeScript. Proficient in managing AI capabilities, evaluation pipelines, and collaborating with cross-functional teams to translate technical needs into actionable solutions.

Highest-signal resume keywords

Node.js DevelopmentTypeScript ProgrammingLLM API ExperienceAWS Cloud InfrastructureRAG System Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software Engineering FundamentalsREST APIsAsync and Promise-Based ConcurrencyTesting Frameworks (Jest, Vitest)Data PipelinesLLM Workflow EvaluationPrompt EngineeringContext Window ManagementFunction CallingTool Use

Soft Skills

Clear CommunicationCoachabilityInitiative

Tools & Technologies

AWS AmplifyClaude CodeCursorOpenAIAnthropic

Certifications & Qualifications

Bachelor’s or Master’s in Computer ScienceAI/MLEngineering

Industry Keywords

RAG MechanicsVector StoresAgent/RAG FrameworksProduction AI FeaturesData Sensitivity

Tech Stack

Tools & technologies

AWSCloudJavaScriptJestNode.jsPythonTypeScript

About the role

Key responsibilities & impact

Add AI capabilities, LLM-powered features, workflows, and interfaces to existing full-stack applications
Build and improve RAG systems with a Senior AI Engineer, including chunking, embeddings, retrieval quality, and evaluation
Manage context windows and model inputs across text, documents, and images
Help design agentic workflows, multi-step LLM pipelines, tool use, and orchestration
Prompt-engineer and evaluate LLM workflows
Write clean, testable services and data pipelines
Translate workflow needs from investment and operations colleagues into concrete technical problems
Work closely with a Senior AI Engineer in an apprenticeship-style role
Take sprint tasks directly and contribute to active RAG or agentic workflow projects
Contribute to evaluation and testing pipelines
Work on a small embedded technology team

Requirements

What you’ll need

Bachelor’s or Master’s in Computer Science, AI/ML, Engineering, or a related field
Solid software engineering fundamentals in Node.js and TypeScript, including REST APIs, async and promise-based concurrency, a testing framework such as Jest or Vitest, and git
Familiarity with AWS Amplify is a plus
Python is a nice to have, especially for RAG and data-heavy work
Exposure to cloud infrastructure, ideally AWS, including Bedrock, Bedrock AgentCore, and Knowledge Bases for Bedrock
Practical experience with LLM APIs such as OpenAI or Anthropic, including function calling and tool use, structured outputs, streaming responses, token usage, and context window limits
Hands-on experience building a real LLM project, prototype, or shipped feature
Experience with LLM-in-the-loop evaluation and testing pipelines, golden datasets, LLM-as-judge scoring, regression tests, promptfoo, Braintrust, or Ragas
Comfort using AI-native development tools such as Claude Code or Cursor
Ability to measure prompt, retrieval, and model changes using evaluation scores, latency, or cost-per-call metrics
Coachability and initiative
Clear communication with non-technical investment and operations professionals
Must be authorized to work in the U.S. without current or future employer sponsorship; employment visa sponsorship is unavailable, including sponsorship after F-1 OPT/CPT
Bonus: familiarity with RAG mechanics, vector stores, agent/RAG frameworks, production AI features, data sensitivity, or MCP

Benefits

Comp & perks

Impact: Build AI systems and autonomous workflows that directly influence investment decisions, portfolio growth, and firm efficiency
Innovation: Be on the leading edge of applying AI/LLMs to venture capital workflows
Collaboration: Work with a lean, entrepreneurial team of investors, technologists, and operators
Growth: Opportunity to expand into broader AI/ML roles as the firm scales its technology platform
Internal advancement opportunities
Comprehensive benefits package including competitive salaries, health and wellness plans, retirement savings options, paid time off, professional development opportunities, and various employee well-being programs