{"id":792738,"url":"https://alion.io/job/heliosintel-applied-intelligence-engineer","title":"Applied Intelligence Engineer","company":{"id":679420,"name":"Helios","domain":"heliosintel.ai","url":"https://alion.io/company/heliosintel","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"Industrial Engineering","role_family":"Industrial Engineering","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":165000,"max":225000,"currency":"USD","period":"year","gross":null,"usd_annual":225000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Datadog","optional":false},{"name":"Function Calling","optional":false},{"name":"Hallucination","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"TypeScript","optional":false},{"name":"CMMC","optional":true},{"name":"FedRAMP","optional":true},{"name":"ISO 27001","optional":true},{"name":"Knowledge Graph","optional":true},{"name":"Semantic Search","optional":true},{"name":"SOC 2","optional":true}],"status":"live","first_seen_at":"2026-08-24T21:31:32Z","employer_posted_date":"2026-08-24","last_verified_at":"2026-10-23T01:33:09Z","board_verified":true,"closed_at":null,"days_open":59,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":59},"description":"Applied Intelligence Engineer - Forward Deployed\nNew York City | Full-time | On-site in SoHo, five days per week\nFrequent domestic and international travel\nReports to the CTO and works directly with the founding team\nABOUT HELIOS\nHelios is building a new kind of company to solve America’s hardest problems, starting with the government interaction layer.\nGovernment 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.\nOur 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.\nWe 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.\nTHE ROLE\nWe are hiring an Applied Intelligence Engineer to turn complex institutional problems into working software.\nYou 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.\nThis 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.\nYou 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.\nAs an early member of this function, you will also help define how Helios delivers applied intelligence systems. Your job is not only to make individual deployments successful, but to turn what we learn in the field into reusable product capabilities, technical infrastructure, and operating playbooks that allow Helios to deploy faster and at greater scale.\nWHAT YOU WILL OWN\nMission Discovery and Solution Design\nWork directly with customer leaders, operators, technical teams, and end users to understand their objectives, workflows, data, constraints, and measures of success.\n\nMove beyond stated feature requests to identify the underlying operational problem and determine what system should actually be built.\n\nMap complex environments across people, processes, data sources, existing software, decision rights, security requirements, and organizational dependencies.\n\nTranslate ambiguous mission and business needs into clear technical requirements, deployment plans, system architectures, milestones, and ownership.\n\nDesign solutions that combine Proxi’s core capabilities with customer-specific data, integrations, workflows, interfaces, and decision-support requirements.\n\nEstablish a clear definition of success for each deployment, including technical performance, user adoption, operational outcomes, and long-term maintainability.\n\nIdentify technical, security, data, adoption, and organizational risks early and develop practical plans to address them.\n\nEnd-to-End Deployments\nOwn deployments from initial discovery and technical scoping through architecture, development, testing, go-live, adoption, and expansion.\n\nConfigure and extend Proxi for specific customer missions, organizational structures, information environments, and operating workflows.\n\nBuild production-quality applications, services, integrations, data pipelines, internal tools, and user experiences required to make each deployment successful.\n\nIngest and normalize large volumes of structured and unstructured data from customer systems, public sources, document repositories, APIs, databases, and other environments.\n\nIntegrate Helios systems with existing enterprise and government technology, including identity providers, data platforms, document systems, APIs, and legacy infrastructure.\n\nDesign and implement reliable workflows for search, retrieval, analysis, monitoring, alerting, reporting, and human review.\n\nBuild and evaluate AI agents that can reason across complex information environments while maintaining source provenance, traceability, and appropriate human control.\n\nTake responsibility for getting systems into the hands of real users and ensuring they work under real operational conditions.\n\nAI and Data Systems\nBuild across the application stack, including backend services, data infrastructure, AI orchestration, APIs, and customer-facing interfaces.\n\nDevelop retrieval, ranking, reasoning, and agentic workflows over complex customer and public-sector information.\n\nDesign data models, ontologies, and knowledge structures that reflect how a customer’s mission and organization actually operate.\n\nBuild evaluation frameworks that measure accuracy, reliability, relevance, latency, and user value rather than relying on anecdotal feedback.\n\nImplement safeguards for hallucination, weak sourcing, improper tool use, and other failure modes in production AI systems.\n\nImprove system performance through better data pipelines, retrieval strategies, prompts, tools, models, and product workflows.\n\nMonitor deployed systems, investigate failures, and resolve issues quickly when performance falls below the required standard.\n\nMake pragmatic technical decisions about when to use an existing platform capability, when to configure it, and when to build something new.\n\nSecure and Reliable Delivery\nDesign deployments for sensitive, regulated, and high-stakes environments.\n\nWork with customer security, privacy, legal, compliance, and IT teams to move deployments from review to production.\n\nImplement appropriate controls for identity, permissions, data access, encryption, auditability, logging, retention, and system monitoring.\n\nAdapt architectures to customer-specific requirements around data residency, network access, cloud infrastructure, and deployment environments.\n\nProduce clear technical documentation, system diagrams, data-flow descriptions, security materials, and implementation plans.\n\nEnsure that prototypes and pilots have a credible path to secure, maintainable, production-scale systems.\n\nTreat customer data, access, and operational information with exceptional care and discretion.\n\nCustomer Technical Leadership\nServe as a trusted technical counterpart to senior government officials, agency technology leaders, enterprise executives, security teams, engineers, analysts, and frontline users.\n\nLead technical discovery sessions, architecture reviews, implementation workshops, demonstrations, testing sessions, and deployment updates.\n\nExplain complicated technical decisions clearly to non-technical stakeholders without obscuring risks or tradeoffs.\n\nEarn customer trust by being responsive, prepared, candid, and accountable for outcomes.\n\nMaintain a clear view of open issues, technical dependencies, upcoming milestones, decisions, owners, and next actions across every deployment.\n\nStay close to users after go-live, observe how the system performs in practice, and rapidly address adoption barriers and emerging requirements.\n\nCoordinate closely with Helios product, engineering, customer success, and company leadership so commitments are realistic and consistently delivered.\n\nSupport technical discovery and solution design during important prospective customer engagements when required.\n\nProductization and Scale\nTranslate repeated customer needs into reusable product features, APIs, data models, connectors, deployment patterns, and internal tools.\n\nDistinguish strategically valuable product capabilities from customer-specific requirements that should remain isolated.\n\nBring structured field insights into product and engineering decisions, supported by evidence from actual deployments and user behavior.\n\nBuild the technical and operational infrastructure that makes each successive deployment faster, safer, and more repeatable.\n\nCreate deployment templates, testing frameworks, technical documentation, implementation playbooks, and reusable components.\n\nReduce the amount of bespoke work required to deliver sophisticated systems without compromising customer outcomes.\n\nHelp define how applied intelligence engineering works with product, engineering, customer success, security, and commercial teams.\n\nContribute directly to the core Proxi platform when field requirements should become permanent product capabilities.\n\nWHAT SUCCESS LOOKS LIKE\nCustomers move from an ambiguous mission problem to a secure, working production system with clear operational value.\n\nDeployments reach meaningful use quickly without creating fragile systems or unmanageable technical debt.\n\nCustomer data, integrations, permissions, and workflows operate reliably under real-world conditions.\n\nUsers trust the system’s outputs because they are relevant, explainable, traceable, and grounded in authoritative information.\n\nTechnical, security, and organizational risks are identified early rather than discovered at the end of a deployment.\n\nCustomers experience Helios as highly technical, responsive, credible, and accountable.\n\nProduct and engineering teams receive clear, prioritized insights from the field rather than a stream of unstructured feature requests.\n\nCapabilities developed for individual deployments become reusable improvements to the broader Proxi platform where appropriate.\n\nEach new deployment becomes faster and more predictable because of the systems, tooling, and practices you create.\n\nStrategic deployments lead to sustained adoption, expanded use cases, and long-term customer relationships.\n\nYOU MIGHT BE A FIT IF YOU\nHave 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.\n\nAre a strong generalist engineer who can independently design and ship production-quality software across multiple parts of the stack.\n\nAre fluent in Python, TypeScript, or comparable modern languages and are comfortable working with APIs, databases, cloud infrastructure, data pipelines, and modern web applications.\n\nHave built or deployed production AI systems using language models, retrieval systems, agentic workflows, tool calling, evaluations, or related technologies.\n\nUnderstand that production AI requires rigorous data, evaluation, observability, security, and user-experience work, not just prompt engineering.\n\nCan quickly understand an unfamiliar institution, workflow, data environment, or mission area and translate it into a coherent technical system.\n\nHave experience integrating software with complex enterprise systems, fragmented data sources, identity infrastructure, and legacy technology.\n\nCan communicate as effectively with senior executives and government leaders as you can with security teams, engineers, and operators.\n\nAre comfortable taking ownership of a loosely defined problem and driving it through discovery, development, deployment, and adoption.\n\nMake sound technical tradeoffs under time pressure without losing sight of security, reliability, or maintainability.\n\nWrite clear technical requirements, deployment plans, documentation, decision records, and customer communications.\n\nAre highly organized and can manage 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