AI Software Engineer Jobs

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Design, build, ship, and maintain core capabilities for North’s Agents & Automations platform. Build product and platform features that help users create, run, debug, evaluate, and improve agents and automations. Own features end-to-end, from technical design through implementation, testing, launch, and iteration. Work across the stack, from frontend product surfaces to backend systems, depending on what the product needs. Make practical technical decisions that balance speed, quality, depth, and user impact. Collaborate closely with product, design, modelling, customer-facing teams, and other engineers to define the right outcomes and ship measurable improvements. Use AI actively in your work, while staying intellectually engaged and accountable for the quality and reliability of what you ship.

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Develop low-level drivers for the sensors or actuators of robots, develop the OS and middleware of the robots, integrate embedded algorithms such as Guidance, Navigation, Control, and Computer Vision, optimize runtime of algorithms on various hardware accelerators like GPU, TPU, DSp, develop the backbone of a command and control system for massive data ingestion and processing, develop a web-based front-end to display theatre of operations and allow mission conduction, build internal tools to improve efficiency and reduce technical debt, develop connectors between existing company tools like ERP, MES, PLM, implement code into production-ready environments, ensure seamless integration with Harmattan AI’s systems, conduct rigorous code reviews, test algorithms in real-world environments, develop monitoring tools, track model performance and continuously improve deployed solutions, collaborate closely with other hardware and software teams to align development with system requirements, and communicate findings effectively to stakeholders.

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As a Software Engineer on Knowledge Systems, you will help build systems that understand what is true about the world by extracting, connecting, retrieving, and reasoning over knowledge from the web and beyond to enable AI agents to answer questions with unprecedented precision and completeness.

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Design and deliver production-grade AI agents that are highly performant, reliable, and intuitive, driving revenue directly to Sierra's growth across industries like finance, healthcare, and commerce. Take complete ownership and autonomy in the Agent Development Life Cycle from initial pilot through deployment and continuous iteration, including building, tuning, and evolving AI agents in production environments while defining best practices. Work directly with leaders of large enterprises and cutting-edge startups to understand their business challenges and develop AI agents that transform their operations at scale. Guide the evolution of Sierra's core platform through customer interaction, surfacing unmet needs, prototyping new tools and features, and collaborating with research, product, and platform teams to shape AI agent development and Sierra's products.

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Design and build scalable backend systems powering AI Agents that operate in real-time enterprise environments. Develop agent orchestration frameworks involving multi-step reasoning, tool usage, and decisioning workflows. Build systems for agent memory, context management, and state persistence across interactions. Architect low-latency inference pipelines integrating Large Language Models, Small Language Models, and external tools/services. Implement evaluation frameworks to measure agent performance, accuracy, and reliability. Enable continuous improvement loops for AI agents in production including feedback, retraining, and deployment. Design and manage event-driven, asynchronous workflows for complex agent tasks. Optimize systems for high throughput, low latency, and cost-efficient inference at scale. Build and maintain robust APIs and service layers (REST/gRPC) for agent capabilities. Partner closely with Applied AI/ML teams to productionize models and agent behaviors. Collaborate with Product and Solutions teams to translate real customer workflows into agentic systems. Drive best practices in observability, monitoring, safety, and guardrails for AI systems. Contribute to architecture decisions for scaling multi-tenant, enterprise-grade AI platforms.

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Build end-to-end product experiences that span frontend applications, backend services, agent workflows, cloud infrastructure, and developer tooling. Design AI-powered workflows that generalize across a wide variety of software engineering teams, languages, codebases, and development practices. Discover and implement novel ways to apply AI to eliminate friction throughout the software development lifecycle. Partner closely with product, design, and research to understand developer needs and rapidly translate insights into shipped product improvements. Work directly with users—including developers at OpenAI, open-source contributors, startups, and large enterprises—to understand pain points and validate solutions. Improve the reliability, observability, scalability, and performance of the systems and workflows you build.

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Build core primitives end to end including entity ownership, audit, authorization, and orchestration, ensuring the right actions are the default and incorrect actions are difficult. Own the domain model by turning Fluidstack's concepts of power, datacenters, and chips into composable entities that remain durable over time. Define interactions with external systems by interfacing with vendor systems and ingesting domain-specific formats such as KMZ, BIM, Revit, and vendor documents. Enable AI agents to be first-class operators of Fluidstack's systems by providing tools, guardrails, and audit trails to allow safe and effective operation beyond mere advice.

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As a Senior Full Stack Engineer at Siena, you will own meaningful parts of the platform end to end, taking ambiguous problems and working out the right approach to ship reliable, high-performance systems that real brands depend on every day. You will own features and systems across the full stack including frontend, backend, and infrastructure from problem definition through production. You will partner with product to break down ambiguous scope and ship in iterative, high-impact releases, make real architectural and design decisions in your area and explain the reasoning to the team, and integrate cutting-edge language models into enterprise customer workflows where reliability and safety are critical. You will solve hard engineering problems including API performance, microservices, and scaling across channels and brands. Additionally, you will maintain and improve AWS infrastructure with a DevOps mindset and contribute to raising the bar around you by sharing knowledge, reviewing thoughtfully, and helping teammates level up.

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Design, develop, and operate backend systems for domain-specific collection search services including news, places, securities, sports, music, and movies. Design and standardize search architectures based on OpenSearch and MongoDB Atlas, including indexing and retrieval structures, to enable rapid expansion of new collections. Analyze search quality and maintain metrics such as nDCG, recall, MRR, and CTR to improve search accuracy, latency, and handle failure cases. Develop and fine-tune ranking models, reranking, embeddings, semantic search, and recommendation logic, focusing on top accuracy for priority collections. Build robust backend infrastructure required for stable production operation, including API contracts, caches, configuration registries, and administrative APIs. Lead technical decision-making processes, conduct design reviews within the team, and address complex problems by improving reusable systems.

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Design and deliver production-grade AI agents that are highly performant, reliable, and intuitive, which are central and mission-critical to Sierra's growth across industries like finance, healthcare, and commerce. Take complete ownership and autonomy over the Agent Development Life Cycle (ADLC) from initial pilot through deployment and continuous iteration, including building, tuning, and evolving AI agents in production environments while defining best practices for ADLC. Partner with leaders at large enterprises and cutting-edge startups to understand their business challenges and build AI agents that transform their operations at scale. Collaborate with customers to guide the evolution of Sierra's core platform by surfacing unmet needs, prototyping new tools and features, and working with research, product, and platform teams to shape the future of AI agent development and Sierra's product.