Job description

About TechTorch At TechTorch, we’re building the future of intelligent work. Our mission is to help companies design, build, and deploy AI agents that automate complex, real-world workflows — delivering reliability, measurable ROI, and massive efficiency gains. Here, you won’t just be playing with prompts or running endless proofs of concept. You’ll ship production-grade AI systems that solve real problems across industries. You’ll join a hands-on, fast-moving, ownership-driven team that thrives on building quickly, iterating fast, and seeing results in days — not months. Role overview We’re looking for an AI Developer who can design, implement, and deploy agentic systems that actually work in production. If you’ve been building AI agents for the last couple of years and love the challenge of getting things done fast — this is your place. This is not a research role. It’s about building, testing, and shipping real AI products that deliver measurable business value. What you’ll do - Design and implement multi-step AI agents and orchestration workflows in Python - Build using LangGraph, LangChain, n8n, AWS Bedrock, and similar tools - Integrate and evaluate top models (Gemini, GPT, Claude, etc.) - Connect agents to real systems (APIs, SaaS apps, webhooks, queues, events) - Implement memory, retrieval, and planning for reliable agent behavior - Take prototypes to production — with CI/CD, containers, and cloud deployment - Build internal SDKs and reusable agent templates to speed up delivery - Instrument everything — logging, tracing, guardrails, evaluation - Work directly with clients to capture requirements, run experiments, and iterate fast - Apply best practices for security, privacy, and safety in all deployments What you bring - 2+ years of hands-on experience building and shipping AI agents or complex automations - Strong Python skills (async, testing, packaging) - Experience with LangGraph or LangChain, plus orchestration tools (n8n, Bedrock, Airflow, Prefect, Temporal, etc.) - Familiarity with OpenAI, Gemini, Claude, or similar model ecosystems - Solid data foundations: embeddings, RAG, chunking, indexing - Software engineering fundamentals: Git, CI/CD, Docker, AWS - TypeScript, FastAPI, Node.js, Supabase, or observability tools (Langfuse, W&B, OpenTelemetry) How you work - You own your outcomes — from idea to deployment - You’re proactive, adaptable, and thrive in fast-changing environments - You like moving fast, but never at the cost of quality - You communicate clearly and love solving problems collaboratively Our Values Client First — We focus relentlessly on delivering outcomes that create value for our clients. We, Not Me — We win together. Collaboration drives transformation at scale. Get Stuff Done — We execute with speed and precision — because in PE, time matters. AI First — We embed AI at the core, enabling scalable, high-leverage solutions. Own It — We take accountability for results, delivering on what we promise. Agile mindset — We adapt quickly and proactively seek better ways to move forward. What We Offer - Work on real, high-impact AI systems — not just demos - Exposure to Fortune 500 and private equity clients - Remote-first and flexible — we care about results, not hours - Fast recruitment process — we move as quickly as you do - Career growth, certifications, and access to leading AI tech

Requirements

Must-haves

We’re looking for an AI Developer who can design, implement, and deploy agentic systems that actually work in production.
If you’ve been building AI agents for the last couple of years and love the challenge of getting things done fast — this is your place.
This is not a research role. It’s about building, testing, and shipping real AI products that deliver measurable business value.
What you’ll do
Design and implement multi-step AI agents and orchestration workflows in Python
Build using LangGraph, LangChain, n8n, AWS Bedrock, and similar tools
Integrate and evaluate top models (Gemini, GPT, Claude, etc.)
Connect agents to real systems (APIs, SaaS apps, webhooks, queues, events)
Implement memory, retrieval, and planning for reliable agent behavior
Take prototypes to production — with CI/CD, containers, and cloud deployment
Build internal SDKs and reusable agent templates to speed up delivery
Instrument everything — logging, tracing, guardrails, evaluation
Work directly with clients to capture requirements, run experiments, and iterate fast
Apply best practices for security, privacy, and safety in all deployments
2+ years of hands-on experience building and shipping AI agents or complex automations
Strong Python skills (async, testing, packaging)
Experience with LangGraph or LangChain, plus orchestration tools (n8n, Bedrock, Airflow, Prefect, Temporal, etc.)
Familiarity with OpenAI, Gemini, Claude, or similar model ecosystems
Solid data foundations: embeddings, RAG, chunking, indexing
Software engineering fundamentals: Git, CI/CD, Docker, AWS
TypeScript, FastAPI, Node.js, Supabase, or observability tools (Langfuse, W&B, OpenTelemetry)
How you work
You own your outcomes — from idea to deployment
You’re proactive, adaptable, and thrive in fast-changing environments

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aipythonawsci/cddockertypescriptnode.jsagile

Platform: ashby
Effort: quick