AI Software Engineer Jobs

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Conceptualise scripts based on current production needs and centred around existing AI characters. Create narrative-driven, longform video content, including stylized and explicit NSFW visuals, with a strong focus on storytelling, atmosphere, and visual coherence throughout. Own and manage end-to-end AI video production workflows, from ideation and prompting to generation, editing, and post-production. Work extensively with ComfyUI pipelines, building, customizing, and optimizing node-based workflows for image and video generation. Utilize tools such as Stable Diffusion (AUTOMATIC1111), ComfyUI, Runway, and other AI video platforms to produce high-quality visual sequences. Develop and maintain consistent character appearance, style, and scene continuity across longer narratives using advanced techniques. Integrate motion graphic design and colour correction to deliver cohesive final outputs. Experiment rapidly with new AI models, tools, and techniques, incorporating them into production workflows and sharing skills with the rest of the team. Align with your Content Lead’s creative direction while maintaining a high degree of autonomy in execution and technical decision-making. Continuously refine workflows for efficiency, scalability, and output quality.

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Apply software engineering skills to design and develop AI video editing products; prototype and craft innovative products for prosumers and enterprise customers; work with cross-functional teams to brainstorm, plan, and deploy product features; design and implement A/B tests to understand the impact of changes, using data-driven insights to inform decisions and strategy adjustments.

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As a Senior Staff Software Engineer at Ironclad, you will serve as the Technical Lead Architect and owner of Ironclad’s document and record service, driving the technical strategy and decisions to ensure reliability, scalability, and performance. You will partner across engineering teams to ensure the document service unlocks new feature capabilities and AI innovation. You will mentor and provide thoughtful feedback to other engineers and cultivate a culture of engineering excellence. Additionally, you will collaborate cross-functionally with product managers, designers, and other engineers to spec, design, and build features and systems. You will partner with quality engineers to define, build, and maintain testing strategies. You will also participate in interviewing and recruiting talented engineers to Ironclad. Your work will involve building on a modern technology stack including TypeScript, Node.js, PostgreSQL, Temporal, and Docker containers in Kubernetes on Google Cloud Platform, and applying AI tools and features to power the future of contract intelligence.

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The responsibilities include improving systems that ensure inference engine releases are correct, performant, and regression-free by evolving tooling and infrastructure for deploy gate validation; bringing rigor to release, validation, branching, and deployment processes across the inference stack; improving canary, async, and large-scale validation workflows for inference systems; hardening CI, testing, and validation infrastructure so failures are actionable and trustworthy; reducing noisy or flaky failures caused by infrastructure instability, GPU scheduling, or test environment issues; building automation for failure triage, ownership detection, debugging, and escalation; partnering closely with inference teams, research developer productivity, engine acceleration, and infrastructure teams to improve release quality and rollout safety; and reducing developer friction in testing, debugging, and release workflows so engineers can move faster with confidence.

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As a Senior Software Engineer on the Agentic Infrastructure team, you will architect and build the core agent orchestration layer including tool use, memory, and multi-step reasoning systems that power AI-driven features for millions of users and employers. You will design evaluation, observability, and reliability frameworks to ensure agent behavior is safe, auditable, and production-ready at scale. Additionally, you will establish engineering standards for agentic development across platform teams and partner with ML, product, and platform engineers to ship agent-powered features from infrastructure to production at a rapid pace.

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As a Senior Software Engineer on the Agentic Infrastructure team at Handshake, you will architect and build the core agent orchestration layer, including tool use, memory, and multi-step reasoning systems that power AI-driven features for over 20 million users and 1 million employers across Handshake's platform. You will design evaluation, observability, and reliability frameworks to ensure that agent behavior is safe, auditable, and production-ready at scale. Additionally, you will establish engineering standards for agentic development across Handshake's platform teams to enable all engineers to build with AI. You will partner with machine learning, product, and platform engineers to ship agent-powered features from infrastructure to production at an accelerated pace.

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Build and maintain data pipelines that ingest real-time market and telemetry data and pass these to forecasting and optimization models. Own production systems using workflow orchestration for battery dispatch and market bidding, ensuring reliability which has direct revenue consequences. Partner with ML and optimization researchers to evaluate and productionize bidding strategies by adding or improving workflow orchestration. Collaborate with data and optimization teams to build reliable data calculations and visualization for settlement calculations, trading operations, and bid strategy evaluation. Contribute to tooling, observability, and patterns to help the team ship and operate software reliably. Make architectural decisions as the platform scales alongside the asset portfolio. Participate in on-call rotation to maintain systems built.

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Design, develop, and refine algorithms focusing on computer vision and spatial data processing including GIS-based data presentation. Design, develop, test, and maintain scalable software applications based on specifications. Collaborate with product managers, designers, and stakeholders to translate requirements into technical solutions. Write clean, efficient, and well-documented code following best practices. Conduct code reviews for quality, maintainability, and performance. Debug and resolve complex software defects timely. Participate in architecture and design discussions aligned with business goals. Collaborate with cross-functional teams on software integration and resolving challenges. Stay updated with emerging technologies and industry trends to improve development practices. Collaborate with QA to define and execute test strategies. Contribute to continuous improvement of development processes, tools, and workflows. Develop and maintain applications for edge and cloud environments. Design and develop advanced features using computer vision for digital twin technology. Analyze performance metrics and iterate to enhance spatial data system accuracy, robustness, and scalability.

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Being a driving force for the team's agentic coding practice by establishing patterns for spec-driven development, context engineering, and multi-agent orchestration that enhance team output. Owning and defining the architecture for AI-powered applications and services to ensure scalability, security, and maintainability across teams. Designing, developing, and deploying backend infrastructure and AI services with a focus on high availability, performance, and reliability. Leading cross-functional initiatives and collaborating with Machine Learning Engineers, Product Managers, and other teams to align technical solutions with business needs. Driving innovation through strategic technical decisions, setting best practices, and mentoring engineers to elevate the team's technical bar. Improving developer experience by building internal tooling, streamlining workflows, and optimizing deployment pipelines. Ensuring seamless data flow by building high-throughput, secure, and scalable data pipelines to support AI model training and deployment. Championing best practices in software engineering with high-quality code, rigorous testing, and well-documented design decisions.

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Be a driving force for the team's agentic coding practice, establishing patterns for spec-driven development, context engineering, and multi-agent orchestration. Design, develop, and maintain AI-powered applications and services focusing on high availability, performance, and reliability. Work closely with Machine Learning Engineers to build AI capabilities from early R&D prototyping to scalable operation in multiple production stacks. Build ML services optimized for low-latency or high-throughput and high cost efficiency. Lead cross-functional initiatives collaborating with Machine Learning Engineers, Product Managers, and other teams to align technical solutions with business needs. Drive innovation by making strategic technical decisions, setting best practices, and mentoring engineers. Improve ML development processes by enhancing internal ML platforms, facilitating data sourcing, and enabling ML observability for deployed services.