Small, experienced engineering teams for product roadmaps.

DeepStack embeds with software companies and technical teams that need more execution capacity. We take ownership of meaningful product, backend, AI, and infrastructure workstreams without adding management overhead.

Start with one or two engineers. Work directly with the people building your product. Continue month-to-month as your roadmap evolves.

Where DeepStack fits

We work primarily with product-led software companies, including B2B SaaS and infrastructure teams. We work well in two situations.

You need a dependable engineering extension

You have a validated software product, a small internal engineering team, and an ongoing roadmap. You need one or two dependable engineers who can understand the system, take ownership, and become a long-term part of the team.

  • Small, technically led engineering organization
  • Paying customers or credible product validation
  • Backend-heavy or technically complex product
  • Long-term roadmap
  • Your CTO or technical founder is directly involved
  • Preference for continuity over interchangeable staffing
Explore the partnership model →

You need to accelerate an existing engineering team

Your internal team is capable, but customer commitments, integrations, platform work, or AI initiatives are moving faster than hiring. DeepStack can own a defined workstream while you continue building the internal organization.

  • Established internal engineering team
  • Commercial traction
  • Growing delivery backlog
  • Workstream that needs clear ownership
  • Hiring cannot meet the required delivery timeline
  • CTO or VP Engineering wants additional execution capacity
See how we add capacity →

What we can own

We focus on meaningful, bounded workstreams with clear ownership.

Product Engineering Extension

Add one or two experienced engineers who embed with your team and own part of the ongoing product roadmap.

  • Backend product development
  • Product features and workflows
  • APIs and integrations
  • Technical debt and system scaling

AI Product Engineering

Build useful AI functionality into an existing product and make it dependable in production.

  • LLM-powered product features
  • AI agents and retrieval / RAG systems
  • Evaluation pipelines
  • Data and ML workflow integration
  • Custom models for tabular data, including XGBoost

Backend & Platform Engineering

Own a backend, infrastructure, or platform workstream when your internal team does not have enough capacity to carry it.

  • Backend services and APIs
  • Data-intensive and distributed systems
  • Infrastructure and reliability
  • Internal platforms and operational tooling

Blockchain Infrastructure Engineering

Specialist engineering for protocol and blockchain infrastructure teams, drawing on DeepStack’s long-standing experience in the space.

  • Protocol and node software
  • Indexing and data infrastructure
  • Wallets and product integrations
  • Distributed systems and protocol tooling

How we work

  1. 1

    Start with a real workstream

    We begin with a meaningful, bounded part of the roadmap, with clear ownership from the start.

  2. 2

    Begin with one or two engineers

    The initial team stays intentionally small, making collaboration easy and helping establish a working rhythm.

  3. 3

    Work inside your team

    We collaborate directly with your CTO or engineering leadership through your existing planning, code-review, and delivery process.

  4. 4

    Take ownership

    DeepStack engineers learn the product, make technical decisions, document their work, and become accountable for delivery.

  5. 5

    Stay as the roadmap evolves

    The engagement continues month-to-month. Scope can evolve as priorities change.

Operating principles

  • Stable engineers and continuity
  • Direct communication with the people doing the work
  • Senior technical oversight
  • Minimal coordination overhead
  • Clear documentation and code review
  • Visible weekly progress
  • Direct delivery communication without added account-management layers
  • Team size aligned with the work

Capabilities that support the work

The workstream comes first. We bring the technical depth needed to own it.

Product and backend

Go, TypeScript, APIs, integrations, business workflows, PostgreSQL, and long-lived product systems.

AI product systems

LLM workflows, agents, retrieval, evaluations, structured extraction, custom models for tabular data, and production AI operations.

Platform and reliability

Distributed systems, data processing, Kubernetes, CI/CD, observability, testing, and operational tooling.

Blockchain infrastructure

Cosmos SDK, Ethereum, EVM-compatible chains, protocol systems, indexing, wallets, and node infrastructure.

Why clients stay

Continuity

The same engineers stay close to the product and accumulate valuable domain knowledge.

Ownership

Bring us a product problem or workstream; we help shape the technical work.

Low management overhead

We work within your existing team and don’t create another layer to manage.

Technical depth

We’re comfortable with complex backend, infrastructure, AI, data, and distributed-systems work.

Flexibility

Start small and continue month-to-month as priorities change.

Long-term orientation

We aim to become a dependable part of your engineering organization as the roadmap evolves.

Experience

Product engineering experience across backend systems, AI products, distributed systems, and blockchain infrastructure for US software and infrastructure companies.

  • Almost 25 years of product engineering experience
  • Long-term work with US software startups and product companies
  • Multi-year client relationships built on continuity and trust
  • Blockchain infrastructure experience with Cosmos SDK, Ethereum, and EVM-compatible chains, including multiple chain launches from testnet to mainnet
  • Production experience with AI agents, LLM-powered workflows, and applied machine learning
  • Hands-on backend, distributed-systems, and infrastructure engineering

Specialist infrastructure delivery

Worked on technically complex blockchain infrastructure spanning Cosmos SDK and EVM-compatible chains — protocol-level systems, indexing, and multiple chain launches from testnet to mainnet, requiring deep protocol knowledge and production reliability, sustained over five years.

AI-enabled hiring platform engineering

Embedded with a US-based AI-powered recruitment technology company, contributing to AI agent workflows and candidate evaluation logic alongside backend systems and integrations with third-party applicant tracking platforms. An ongoing engagement, running for about a year and a half to date.

Decentralized network and registry engineering

Joined a decentralized peer-to-peer network project as a core embedded engineer, building its blockchain-backed registry and naming service for application and service discovery, with additional contributions to the network’s compute layer. Engagement ran just over two years.

A good fit

DeepStack may be a strong fit when:

  • You operate a product-led software company or infrastructure team.
  • You already have paying customers or meaningful product validation.
  • Your roadmap extends beyond a short project.
  • You need one or two engineers who can become deeply familiar with the product.
  • You need ownership of a product, backend, AI, or infrastructure workstream.
  • You value continuity and accountability in an external engineering partner.
  • Your CTO, founder, or engineering leader wants direct access to the people doing the work.
  • You’re comfortable collaborating with a distributed engineering team.

Probably not a fit

DeepStack is probably not the right fit for:

  • One-off marketing websites
  • Short fixed-price MVP builds
  • Commodity staff augmentation
  • Large-scale hiring of interchangeable developers
  • Tiny, disconnected tickets with no workstream ownership
  • Primarily visual or design-led projects
  • Projects where you want to fully outsource product ownership
  • Companies choosing primarily on the lowest hourly rate
  • Projects without access to technical decision-makers
  • Work with no meaningful roadmap after the initial delivery

Need one or two engineers you can rely on for the next several years?

Tell us about your product, your internal engineering team, and the part of the roadmap that needs an owner.

Discuss your engineering roadmap

A good first conversation focuses on your roadmap, current engineering capacity, and whether DeepStack is the right long-term fit.