Full Stack AI + Data Engineer

TechTorch is a high-growth enterprise technology consultancy that partners with leading private equity-backed businesses to deliver AI-powered solutions. They are seeking a Full Stack AI + Data Engineer who will own the complete product lifecycle, from discovery and ideation through to production deployment, and be involved in designing and building AI-native systems.

Responsibilities:

• Own the full product lifecycle — from discovery and ideation through system design, build, and production deployment
• Design and build RAG pipelines, agentic workflows, and multi-agent systems using LangGraph and the broader AI agent ecosystem
• Build and compose AI capabilities using MCP servers, Skills, and Plugins — and stay sharp on how these primitives are evolving
• Develop Next.js frontends that make complex AI workflows feel intuitive to end users
• Build Python-based APIs and backend services using FastAPI, with PostgreSQL as the primary data store
• Design and implement automation workflows using Celery, Temporal, or equivalent orchestration tools
• Architect and maintain data pipelines (ETL/ELT), data models, and dbt-based analytics engineering layers
• Set up and own CI/CD pipelines and cloud deployments on AWS and Azure
• Leverage AI-paired programming tools (Claude Code or similar) as a daily accelerator — not as a crutch, but as a force multiplier
• Translate ambiguous client requirements into clear system designs, and communicate trade-offs across both technical and business audiences
• Contribute to reusable internal accelerators and technical assets within the Data Practice

Requirements:

• Production-grade experience across AI engineering, full-stack development, and data — with genuine depth, not just surface familiarity
• RAG pipeline design — retrieval strategies, vector stores, chunking, re-ranking, and evaluation
• Agentic AI systems using LangGraph — multi-agent coordination, tool use, memory, and state management
• Building and composing AI capabilities via MCP servers, Skills, and Plugins
• AI-paired accelerated programming — proficient at using Claude Code or a comparable agentic coding tool as a daily productivity layer
• Python — primary language, used for services, automation, and data work
• FastAPI — async REST API design, dependency injection, testing
• Next.js — component architecture, server-side rendering, state management, and UX sensibility
• PostgreSQL — schema design, query optimization, indexing
• System Design — can architect a system from a blank page: services, boundaries, trade-offs, and scale
• Building automation workflows using Celery or Temporal — task queuing, retries, distributed scheduling
• Event-driven patterns and async processing at the application layer
• ETL/ELT pipeline design — batch, incremental, and event-driven ingestion patterns
• Data pipelining and modeling — dimensional modeling, EDW design, schema governance
• dbt — transformation logic, testing, documentation, and analytics engineering best practices
• CI/CD and deployment — GitHub Actions or equivalent, containerized delivery, environment management
• Exposure to common cloud services on AWS and Azure — compute, storage, managed databases, serverless
• Experience in a consulting or client-delivery environment
• Contributions to open-source AI or data tooling
• Exposure to multi-cloud or hybrid cloud architectures
• Knowledge of MLflow, Weights & Biases, or similar experiment tracking tools
• Familiarity with streaming data patterns (Kafka, Spark Streaming)