Applied Intelligence Engineer

About Helios

Helios is building a new kind of company to solve America’s hardest problems, starting with the government interaction layer. Government shapes every consequential market, but the infrastructure connecting public institutions and private organizations remains fragmented, manual, and difficult to navigate. Helios is rebuilding that layer. Our core platform, Proxi, gives organizations the intelligence they need to understand what government is doing, why it matters, and what to do next. From that foundation, we design and deploy secure, mission-specific systems for government agencies, enterprises, and institutions operating in complex and highly regulated environments. We bring together frontier AI, deep public-sector expertise, and forward-deployed execution. Our team includes leaders and builders from the White House, U.S. Department of State, Datadog, and Microsoft. We are backed by leading institutional investors and trusted by organizations working on high-stakes problems across government and industry.

About the Role

We are hiring an Applied Intelligence Engineer to turn complex institutional problems into working software. You will embed directly with customers, understand how their organizations actually operate, and design and deploy systems that work within their technical, operational, and security constraints. These deployments may take you inside a U.S. federal agency, an international public institution, or a Fortune 50 enterprise. This is not a conventional implementation, solutions engineering, or customer success role. You will write production code, design technical architectures, integrate fragmented data and legacy systems, configure and extend Proxi, and work alongside users through deployment and adoption. When the existing product does not fully solve the problem, you will build what is missing. You will operate at the intersection of engineering, product, and mission delivery. You should be comfortable moving from a meeting with senior government or enterprise leaders to a technical architecture session, then opening the codebase and shipping the solution. As an early member of this function, you will also help define how Helios delivers applied intelligence systems.

Responsibilities

• Mission Discovery and Solution Design
  • Work directly with customer leaders, operators, technical teams, and end users to understand their objectives, workflows, data, constraints, and measures of success.
  • Move beyond stated feature requests to identify the underlying operational problem and determine what system should actually be built.
  • Map complex environments across people, processes, data sources, existing software, decision rights, security requirements, and organizational dependencies.
  • Translate ambiguous mission and business needs into clear technical requirements, deployment plans, system architectures, milestones, and ownership.
  • Design solutions that combine Proxi’s core capabilities with customer-specific data, integrations, workflows, interfaces, and decision-support requirements.
  • Establish a clear definition of success for each deployment, including technical performance, user adoption, operational outcomes, and long-term maintainability.
  • Identify technical, security, data, adoption, and organizational risks early and develop practical plans to address them.
• End-to-End Deployments
  • Own deployments from initial discovery and technical scoping through architecture, development, testing, go-live, adoption, and expansion.
  • Configure and extend Proxi for specific customer missions, organizational structures, information environments, and operating workflows.
  • Build production-quality applications, services, integrations, data pipelines, internal tools, and user experiences required to make each deployment successful.
  • Ingest and normalize large volumes of structured and unstructured data from customer systems, public sources, document repositories, APIs, databases, and other environments.
  • Integrate Helios systems with existing enterprise and government technology, including identity providers, data platforms, document systems, APIs, and legacy infrastructure.
  • Design and implement reliable workflows for search, retrieval, analysis, monitoring, alerting, reporting, and human review.
  • Build and evaluate AI agents that can reason across complex information environments while maintaining source provenance, traceability, and appropriate human control.
  • Take responsibility for getting systems into the hands of real users and ensuring they work under real operational conditions.
• AI and Data Systems
  • Build across the application stack, including backend services, data infrastructure, AI orchestration, APIs, and customer-facing interfaces.
  • Develop retrieval, ranking, reasoning, and agentic workflows over complex customer and public-sector information.
  • Design data models, ontologies, and knowledge structures that reflect how a customer’s mission and organization actually operate.
  • Build evaluation frameworks that measure accuracy, reliability, relevance, latency, and user value rather than relying on anecdotal feedback.
  • Implement safeguards for hallucination, weak sourcing, improper tool use, and other failure modes in production AI systems.
  • Improve system performance through better data pipelines, retrieval strategies, prompts, tools, models, and product workflows.
  • Monitor deployed systems, investigate failures, and resolve issues quickly when performance falls below the required standard.
  • Make pragmatic technical decisions about when to use an existing platform capability, when to configure it, and when to build something new.
• Secure and Reliable Delivery
  • Design deployments for sensitive, regulated, and high-stakes environments.
  • Work with customer security, privacy, legal, compliance, and IT teams to move deployments from review to production.
  • Implement appropriate controls for identity, permissions, data access, encryption, auditability, logging, retention, and system monitoring.
  • Adapt architectures to customer-specific requirements around data residency, network access, cloud infrastructure, and deployment environments.
  • Produce clear technical documentation, system diagrams, data-flow descriptions, security materials, and implementation plans.
  • Ensure that prototypes and pilots have a credible path to secure, maintainable, production-scale systems.
  • Treat customer data, access, and operational information with exceptional care and discretion.
• Customer Technical Leadership
  • Serve as a trusted technical counterpart to senior government officials, agency technology leaders, enterprise executives, security teams, engineers, analysts, and frontline users.
  • Lead technical discovery sessions, architecture reviews, implementation workshops, demonstrations, testing sessions, and deployment updates.
  • Explain complicated technical decisions clearly to non-technical stakeholders without obscuring risks or tradeoffs.
  • Earn customer trust by being responsive, prepared, candid, and accountable for outcomes.
  • Maintain a clear view of open issues, technical dependencies, upcoming milestones, decisions, owners, and next actions across every deployment.
  • Stay close to users after go-live, observe how the system performs in practice, and rapidly address adoption barriers and emerging requirements.
  • Coordinate closely with Helios product, engineering, customer success, and company leadership so commitments are realistic and consistently delivered.
  • Support technical discovery and solution design during important prospective customer engagements when required.
• Productization and Scale
  • Translate repeated customer needs into reusable product features, APIs, data models, connectors, deployment patterns, and internal tools.
  • Distinguish strategically valuable product capabilities from customer-specific requirements that should remain isolated.
  • Bring structured field insights into product and engineering decisions, supported by evidence from actual deployments and user behavior.
  • Build the technical and operational infrastructure that makes each successive deployment faster, safer, and more repeatable.
  • Create deployment templates, testing frameworks, technical documentation, implementation playbooks, and reusable components.
  • Reduce the amount of bespoke work required to deliver sophisticated systems without compromising customer outcomes.
  • Help define how applied intelligence engineering works with product, engineering, customer success, security, and commercial teams.
  • Contribute directly to the core Proxi platform when field requirements should become permanent product capabilities.

What Success Looks Like

• Customers move from an ambiguous mission problem to a secure, working production system with clear operational value.
• Deployments reach meaningful use quickly without creating fragile systems or unmanageable technical debt.
• Customer data, integrations, permissions, and workflows operate reliably under real-world conditions.
• Users trust the system’s outputs because they are relevant, explainable, traceable, and grounded in authoritative information.
• Technical, security, and organizational risks are identified early rather than discovered at the end of a deployment.
• Customers experience Helios as highly technical, responsive, credible, and accountable.
• Product and engineering teams receive clear, prioritized insights from the field rather than a stream of unstructured feature requests.
• Capabilities developed for individual deployments become reusable improvements to the broader Proxi platform where appropriate.
• Each new deployment becomes faster and more predictable because of the systems, tooling, and practices you create.
• Strategic deployments lead to sustained adoption, expanded use cases, and long-term customer relationships.

Requirements

• Have 5 or more years of experience in software engineering, applied AI, solutions architecture, technical implementation, or another role involving significant production engineering and customer ownership.
• Are a strong generalist engineer who can independently design and ship production-quality software across multiple parts of the stack.
• Are fluent in Python, TypeScript, or comparable modern languages and are comfortable working with APIs, databases, cloud infrastructure, data pipelines, and modern web applications.
• Have built or deployed production AI systems using language models, retrieval systems, agentic workflows, tool calling, evaluations, or related technologies.
• Understand that production AI requires rigorous data, evaluation, observability, security, and user-experience work, not just prompt engineering.
• Can quickly understand an unfamiliar institution, workflow, data environment, or mission area and translate it into a coherent technical system.
• Have experience integrating software with complex enterprise systems, fragmented data sources, identity infrastructure, and legacy technology.
• Can communicate as effectively with senior executives and government leaders as you can with security teams, engineers, and operators.
• Are comfortable taking ownership of a loosely defined problem and driving it through discovery, development, deployment, and adoption.
• Make sound technical tradeoffs under time pressure without losing sight of security, reliability, or maintainability.
• Write clear technical requirements, deployment plans, documentation, decision records, and customer communications.
• Are highly organized and can manage multiple technical workstreams, stakeholders, dependencies, and deadlines simultaneously.

Schedule

On-site in SoHo, five days per week. Frequent domestic and international travel.

Reports to the CTO and works directly with the founding team.