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Nexxa.ai is seeking a Technical Project Manager to drive project execution excellence across Applied AI and Core Engineering teams. In this hands-on role, you will own project decomposition, estimation, and timeline management while coordinating cross-functional teams, surfacing blockers, and ensuring smooth execution from development through deployment.
You'll operate at the intersection of product and engineering, managing competing demands and executing against shared priorities in a fast-paced, ambiguous environment. This is foundational work critical to business delivery.
Key Responsibilities:
• Manage project timelines, scope, estimation, decomposition, and dependencies across development initiatives
• Coordinate core engineering, DevOps, testing, and client delivery teams
• Maintain project tracking and status reporting with clear sprint goals and visible dependencies
• Provide technical triage on agent orchestration, infrastructure automation, workflow orchestration, CI/CD pipelines, and platform architecture—asking good questions and spotting risks rather than requiring deep expertise
• Anticipate and escalate blockers to keep projects on track
• Surface risks early and communicate status clearly to stakeholders
About Nexxa: Nexxa builds specialized AI agents for industrial engineers, automating complex workflows in heavy industries including rail, energy, construction, and manufacturing. The company is post-seed, well-funded, and focused on delivery excellence with a direct, technical, outcome-focused culture that ships with bias toward action.
Requirements:
• 2–4 years of program/project management experience, ideally in technical environments (software, infrastructure, or consulting)
• Proven track record managing project timelines and tracking progress across distributed teams
• Clear written and verbal communication; concise and precise in writing and feedback
• Ability to thrive in ambiguity; asks good questions and escalates appropriately
• Familiarity with AI development, agent orchestration, and workflow concepts (multi-step agentic workflows, state management, error handling)
• Basic understanding of infrastructure-as-code principles and ability to reason about reproducibility, versioning, and scalability
• Understanding of durable, distributed workflow execution and how orchestration layers fit into broader architecture
• Knowledge of deployment pipelines, infrastructure automation, release management, testing strategies, and deployment workflows
• Understanding of how user experience impacts adoption and team velocity
• Strong organizational and framework-driven prioritization skills
• Data-driven mindset; tracks and references metrics to inform decisions
• Attention to detail; documents work clearly and catches gaps in communication or scope
• Comfort with rapid iteration and learning; moves fast and owns mistakes
Nice to Have:
• Experience managing AI/ML projects or infrastructure teams
• Background in startup or scale-up environments
• Hands-on coding experience with AI agents, LLM applications, or Python
• Familiarity with distributed systems concepts or microservices architecture
• Experience with Confluence, Jira, Azure DevOps, or similar tools
• Comfort working in technical environments (terminals, APIs, automation scripting)
