Steinn Labs places senior AI engineers remotely inside your team, on a monthly basis. They work like your own engineers, in your repos, on your roadmap, against your deadlines, and they leave behind systems your team can own.
Tell us what you want shipped. We'll tell you who you need and when they can start. Usually within a week. Talk to us.
The Steinn Labs team · Pune · Remote-first · Building since 2018
Six senior roles. Hire one, hire a pod, or hire the whole bench. Each engineer comes with a deep, opinionated stack and the seniority to use it well.
Designs multi-agent topologies, orchestration layers, and long-horizon planning systems. Owns the end-to-end agent architecture across teams.
Agent frameworks
Orchestration & protocols
LLM platforms
Connects LLMs and agents to enterprise data systems, APIs, and SaaS platforms. Builds reliable tool-use pipelines and data connectors.
Agent & RAG tooling
Enterprise integrations
APIs & protocols
Builds the backend infrastructure that powers agents: memory stores, vector databases, task queues, and stateful session management.
Memory & vector stores
Languages & runtimes
Infrastructure
Owns CI/CD pipelines for agent deployments, cost monitoring, eval-driven releases, and production observability of LLM workloads.
Observability & evals
Deployment
Cloud platforms
Enforces guardrails, prevents prompt injection and data exfiltration, ensures compliance with enterprise AI governance and regulatory frameworks.
Guardrails & safety
Governance & compliance
Security engineering
Builds voice and chat interfaces powered by agents: dialogue management, persona design, context handling, and multimodal pipelines.
Conversation & voice
Frontend & UI
Prompt & persona engineering
You pick the engineers you need: an agent architect, an LLM integration engineer, an MLOps lead, or a full pod. They start within a week. They join your Slack, your repo, your standups. They report to your engineering manager, not ours.
They don't just take tickets. They help you shape AI workflows and processes from the ground up: where agents fit in your product, how to evaluate them, what to build in-house versus buy, how your team will own the system once it's live. Senior judgement, in your room, every week.
Month to month. Scale the team up when you're shipping a new product, scale it down when you're not. No long contracts, no minimum spend tiers, no per-seat licensing for "AI platforms" you'll never log into.
You get senior partners who write code. You get them this month. You get to keep what they build.
We've shipped enough of these systems to know what works and what looks good in a pitch. Here's what we actually believe.
Steinn engineers join your tools, your standups, your sprints. They sit inside your team structure and own outcomes, not just deliverables. No status decks. No invoices for thinking.
Agent architecture. LLM integration. Vector infrastructure. Observability. Security and compliance. Every layer, covered. So you don't have to hire six specialists separately and pray they get along.
No six-month discovery phases. We use proven frameworks. LangGraph, AWS AgentCore, Semantic Kernel, CrewAI, and we've already made the expensive mistakes so you won't have to.
Your data lives in Salesforce, SAP, SharePoint, and a 2009 internal portal nobody wants to touch. We connect to all of it. Real integrations. Real security. Real compliance with GDPR, HIPAA, SOC 2, and the EU AI Act.
Most AI projects break at the seams: a prototype that works in a notebook, a model nobody can monitor, an agent nobody can audit. Our engineers own the whole stack, from the first prompt to the production trace.
Multi-agent systems, planning loops, tool use, memory, hand-offs. Built on LangGraph, CrewAI, AutoGen, Semantic Kernel, or AWS AgentCore depending on what fits your stack.
Model selection, prompt engineering, structured outputs, function calling, fallback chains, cost-aware routing across OpenAI, Anthropic, Bedrock, Vertex, and open-weight models.
Vector stores, hybrid search, chunking strategies, re-ranking, long-term agent memory. We pick pgvector, Pinecone, Weaviate, or Qdrant based on your scale, not our preferences.
Ingestion, ETL, embeddings refresh, evaluation datasets. We connect to Salesforce, SAP, ServiceNow, SharePoint, Snowflake, and the messy internal systems no one wants to touch.
Production services around your agents: auth, rate limiting, queues, webhooks, streaming. Python, TypeScript, Go. Whatever your team already runs.
Deployment on AWS, Azure, GCP, or on-prem. CI/CD for prompts and agents, model versioning, canary releases, GPU scheduling, cost controls.
Tracing every agent run with LangSmith, Arize Phoenix, Helicone, or Braintrust. Offline evals, online metrics, regression suites. You see what the agent did and why.
Prompt injection defence, PII redaction, guardrails, audit logs, role-based access. Mapped to OWASP LLM Top 10, SOC 2, HIPAA, GDPR, and EU AI Act requirements.
One pod. One point of accountability. No hand-offs to a "platform team" that doesn't exist yet.
We get asked this a lot, so here it is in one place. The tools, frameworks, and platforms our engineers ship on every day. If you already use it, we already know it.
Agent frameworks
Orchestration
LLM platforms
Memory & retrieval
Enterprise connectors
Observability
Security & compliance
No slideware, no strategy decks. Six concrete things show up in your company by the time we're done.
Every engagement ships working systems into your stack. Code in your repo, agents in your runtime, observability you own.
Models, prompts, evals, and orchestration live in your accounts. No black boxes, no lock-in to ours. You can fire us and keep running.
Architecture decisions, evals, failure modes, and on-call playbooks written down. New engineers ramp in days, not quarters.
We instrument what the agent replaces or accelerates: hours saved, tickets closed, revenue unlocked. Reported monthly.
We pair, review, and teach as we build. By the end of the engagement your team owns the patterns and can ship the next one alone.
If you want, one of our engineers stays embedded as Orbit, keeping the system healthy while your team builds on top of it.
Real founders. Real products. Real users. Here's what happens when you work with a team that actually delivers.
Manufacturing
A multi-agent AI system deployed on-premise for a polymer injection moulding manufacturer, using LangGraph, self-hosted small language models, and Langfuse observability.
Crypto, Fintech
CoinDCX hired our senior Flutter engineer to help them migrate their older hybrid app to a fully new, blazing fast Flutter app.
Telecom
A major Australian telecommunications company hired our remote team to rapidly develop a comprehensive customer-facing application.
Still comparing options? Here's how we stack up against the alternatives ↓
We work with engineering leaders, CTOs, and heads of product who have a real codebase, a real roadmap, and a real need for senior AI engineers they can't hire fast enough, whether that's to ship a planned roadmap or to figure out what the AI roadmap should even be.
Treat us as partners, not contractors. Our engineers will challenge a spec, redesign a workflow, push back on a model choice, and sit in the planning meeting before they sit in the repo. Then they ship.
We don't do proofs of concept that go nowhere. We don't write strategy decks for the shelf. We don't sell you a platform.
If you want engineers in your repo by next week, shaping AI workflows and building production systems your team will own, we should talk. If you want a vendor, we'll happily refer you to one.
The name comes from the Old Norse word for stone. We chose it deliberately.
AI moves fast. Hype moves faster. Our engineers are sent in to build things that last, systems that don't collapse when a model changes, a vendor pivots, or your team takes them over six months from now.
Forward-deployed doesn't mean disposable. Our engineers integrate like staff, write code your team can read, and document what they ship. When the engagement ends, you keep the system and the know-how.
That's the whole pitch. Senior engineers, embedded remotely, building AI that holds up.
Send us a short note about what you're shipping and the gap on your team. We'll come back with the right engineers, their availability, and an honest answer on whether we're the right fit. Usually within 24 hours.
No pitch deck. No sales cycle. Just engineers talking to engineers.
Steinn Labs · Pune, India · Remote-first · Building since 2018 · hello@steinnlabs.com
