A trusted engineering team for your long-term product roadmap.

DeepStack provides small, experienced engineering teams to B2B software companies that need reliable execution without adding management overhead. We embed with your internal team, take ownership of meaningful product and backend work, and stay for the long term.

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 well in two situations.

You need a dependable engineering extension

You have a validated B2B 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 take ownership of meaningful, bounded areas of the product — not a queue of disconnected tickets.

Backend and core product systems

Complex business logic, APIs, workflows, performance-sensitive services, and long-lived product modules.

AI-enabled product engineering

AI agents, LLM-powered workflows, evaluation systems, structured data extraction, and AI features that solve real product problems.

Data-intensive applications

Data pipelines, processing systems, analytics foundations, search, structured signals, and machine-learning-backed product decisions.

Infrastructure and production reliability

Deployment systems, Kubernetes-based infrastructure, observability, reliability improvements, CI/CD, testing, and operational tooling.

APIs and enterprise integrations

External APIs, internal platforms, authentication, billing, customer integrations, and product interoperability.

Blockchain infrastructure

Protocol, wallet, indexing, distributed-systems, and blockchain infrastructure work where DeepStack’s specialist experience creates an advantage.

How we work

  1. 1

    Start with a real workstream

    We begin with a meaningful, bounded part of the roadmap — not a vague request for extra developers.

  2. 2

    Begin with one or two engineers

    The initial team stays intentionally small, making collaboration easy and reducing your commitment risk.

  3. 3

    Work inside your team

    We use your existing communication, 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 without repeatedly rebuilding the team or renegotiating projects.

Operating principles

  • Stable engineers rather than frequent rotation
  • Direct communication with the people doing the work
  • Senior technical oversight
  • Minimal coordination overhead
  • Clear documentation and code review
  • Visible weekly progress
  • No unnecessary account-management layers
  • No pressure to expand the team beyond what you need

Why clients stay

Continuity

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

Ownership

You’re not required to break every problem into tightly specified tickets.

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

The goal isn’t to finish a short project and leave. It’s to become a dependable part of your engineering organization.

Experience

More than two decades of product engineering experience, applied to backend systems, AI products, distributed systems, and blockchain infrastructure for US software companies.

  • More than 20 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 B2B software product.
  • 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 backend, product, infrastructure, data, or AI work.
  • You value continuity and accountability more than rapidly adding interchangeable developers.
  • 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
  • Primarily visual or design-led projects
  • 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.