DeepStack builds dependable AI agents, backend systems, and product features. We take ownership of focused projects and ongoing 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.
We work primarily with product-led software companies, including B2B SaaS and infrastructure teams. We work well in two situations.
You have a validated software product, a small internal engineering team, and a defined project or roadmap. You need dependable engineers who can understand the system and take ownership of the work.
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.
We focus on meaningful, bounded workstreams with clear ownership.
Add one or two experienced engineers who embed with your team and own part of the ongoing product roadmap.
Build dependable AI agents that use tools, connect to your systems, and carry out multi-step workflows in production.
Own a backend, infrastructure, or platform workstream when your internal team does not have enough capacity to carry it.
Specialist engineering for protocol and blockchain infrastructure teams, drawing on DeepStack’s long-standing experience in the space.
We begin with a meaningful, bounded part of the roadmap, with clear ownership from the start.
The initial team stays intentionally small, making collaboration easy and helping establish a working rhythm.
We collaborate directly with your CTO or engineering leadership through your existing planning, code-review, and delivery process.
DeepStack engineers learn the product, make technical decisions, document their work, and become accountable for delivery.
The engagement continues month-to-month. Scope can evolve as priorities change.
The workstream comes first. We bring the technical depth needed to own it.
Go, TypeScript, APIs, integrations, business workflows, PostgreSQL, and long-lived product systems.
LLM workflows, agents, retrieval, evaluations, structured extraction, custom models for tabular data, and production AI operations.
Distributed systems, data processing, Kubernetes, CI/CD, observability, testing, and operational tooling.
Cosmos SDK, Ethereum, EVM-compatible chains, protocol systems, indexing, wallets, and node infrastructure.
The same engineers stay close to the product and accumulate valuable domain knowledge.
Bring us a product problem or workstream; we help shape the technical work.
We work within your existing team and don’t create another layer to manage.
We’re comfortable with complex backend, infrastructure, AI, data, and distributed-systems work.
Start small and continue month-to-month as priorities change.
We build maintainable systems and document our work so your team can confidently build on it.
Product engineering experience across backend systems, AI products, distributed systems, and blockchain infrastructure for US software and infrastructure companies.
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.
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.
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.
DeepStack may be a strong fit when:
DeepStack is probably not the right fit for: