Senior Software Engineer, Agent Engineering

This Jobot Job is hosted by:
Merwan Zattam

Salary: $185,000 - $235,000 per year

We are building a new kind of technology company focused on solving complex, high-impact problems, beginning with the way organizations interact with government.

Government influences nearly every consequential market, yet the infrastructure connecting public institutions and private organizations remains fragmented, manual, and difficult to navigate. Our mission is to rebuild that interaction layer.

Our core platform provides organizations with the intelligence they need to understand what government is doing, why it matters, and what actions to take 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 combine frontier AI, deep public-sector expertise, and forward-deployed execution. Our team includes experienced leaders and engineers from major technology companies and senior government organizations. We are backed by leading institutional investors and trusted by organizations working on high-stakes challenges across government and industry.

• Equity / ownership - meaningful upside if the company grows.
• Direct access to founders and CTO - this particular role reports directly to the CTO and works with the founding team.
• Very high technical ownership - owning core agent-runtime infrastructure rather than maintaining a small component of a mature product.
• Frontier agentic-AI work - production agents, long-running workflows, memory, retrieval, model routing, tool use, evaluation and security rather than simply wrapping an LLM API.
• Early-stage impact - engineers joining now can materially influence architecture, engineering standards and product direction.
• Strong founding team - leadership backgrounds include the White House, State Department, Datadog and Microsoft.
• Funded startup - Helios publicly references a $4M seed round, giving you a concrete funding story when discussing the opportunity.
• Interesting customer/mission exposure - the company is building AI systems for government, policy, procurement and other complex/high-stakes environments.
• SoHo / NYC office - attractive for someone who specifically wants an in-person startup environment and direct collaboration.

We are seeking a Staff/Senior Software Engineer specializing in Agent Engineering to advance the agent runtime powering our platform's research, analysis, and action capabilities.

Our agents must be capable of decomposing open-ended objectives, retrieving trustworthy evidence, safely using tools, coordinating long-running work, and producing high-fidelity outputs that remain traceable to their sources.

You will own and improve the systems that make agent behavior reliable in production, including:

• Execution state and orchestration
• Tool use and permissions
• Context and persistent memory
• Model routing
• Failure recovery
• Evaluation and observability
• Security and operational controls

The goal is to enable agents to perform meaningful work over extended periods without losing context, exceeding their authority, silently failing, or producing unsupported conclusions.

You will also advance the platform's reasoning and memory layer, enabling agents to accumulate knowledge, recognize changes, resolve contradictions, and maintain direct source context across workflows.

We're looking for an experienced engineer who has shipped production LLM or agent systems beyond the prototype stage.

You should be comfortable diagnosing nondeterministic failures, establishing clear boundaries between model judgment and deterministic software, and determining when workflows require autonomous execution, human approval, or conventional application logic.

Ideal experience includes:

• Production orchestration of stateful, long-running, and multi-agent workflows
• Tool and action infrastructure with strong contracts, permissions, and approval boundaries
• Retrieval, context engineering, evidence management, and persistent agent memory
• Model-runtime engineering across multiple providers, latency profiles, and deployment environments
• Evaluation, tracing, security, and operational control of nondeterministic AI systems
• Designing reliable systems around LLM behavior in production environments

• Own and advance the platform's agent runtime and the foundational systems used to build new agent-driven products.
• Build…