The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Software Engineer, you will own the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders. You will: Design and implement scalable backend systems for Federal customers using cloud-native AI infrastructure. Build features for agentic systems including multi-layered guardrails and data retrieval optimization. Develop data pipelines and machine learning infrastructure to make data sources accessible by agents. Collaborate with cross-functional teams to execute backend solutions for secure environments. Participate in customer engagements to understand requirements and deliver technical solutions. Define requirements with stakeholders and implement features until they are accepted. Contribute to the platform roadmap and product strategy for the Federal business. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes
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The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Senior Software Engineer, you will lead the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders. You will: Lead the design and implementation of scalable backend systems and distributed architectures for Federal customers. Manage the full lifecycle of feature development from requirement definition to deployment on classified networks. Direct the orchestration of asynchronous agent fleets to meet mission requirements. Lead customer engagements to translate mission needs into technical requirements. Own the communication with stakeholders to ensure implementation meets defined acceptance criteria. Conduct technical reviews and identify risks within machine learning infrastructure and model serving. Drive the platform roadmap by providing technical specifications for Federal product offerings. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and contai
Scale AI is seeking a highly skilled and motivated Software Engineer, Frontier AI Infrastructure to join our dynamic Public Sector Engineering team. As a part of this team, you will own the model inference layer - enabling state of the art models, debugging the latest AI tools, managing networking, debugging latency, and tracking pricing/usage metrics for AI models. You will lead technical discussions on the frontlines with cloud vendors and customers to deliver on critical contracts and to debug platform issues. You will also work upstream with Product to understand features before they break, moving us from "infra-only debugging" to proactive integration testing. You will: Design and implement secure scalable backend systems for Public Sector customers, leveraging Scale's modern and cloud-native AI infrastructure. Own services or systems and define their long-term health goals, while also improving the health of surrounding components Re-architect the stack to run in compliant or restrictive environments. This requires designing swappable components (auth, storage, logging) to meet government/security mandates without breaking the product. You will work with Product to build integration tests that catch issues early, shifting the focus from "infra-only debugging" to preventing failures upstream. Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions. Contribute to the platform roadmap and product strategy for Scale AI's Public Sector business, playing a key role in shaping the future direction of our offerings. Must have: At least an active secret clearance and the ability & willingness to up level to TS/SCI with CI Poly. This is a requirement and candidates will not be considered who do not hold at least a secret clearance Ideally you'd have: Full Stack Development: Proficiency in both front-end and back-end development, including experience with modern web develo
Software Engineer Argentina; Uruguay Software Engineer - Robotics & Autonomous Systems Scale's Robotics business unit is dedicated to solving the data bottleneck in Physical AI across Robotics, Autonomous Vehicles, and Computer Vision. In this role, you'll be a key contributor building production systems for robotics data collection, model training pipelines, and evaluation infrastructure. You'll have the opportunity to own critical parts of our robotics platform, work directly with cutting-edge robotics and AV customers, and shape the future of embodied AI systems. You Will: Own and architect large-scale data processing pipelines for robotics and autonomous vehicle datasets Build ML training and fine-tuning pipelines using Scale's robotics data Work across backend (Python, Node.js , C++), and frontend (React, TypeScript) stacks to build end-to-end solutions Develop tools and real-time systems for robotics data collection, teleoperation, model evaluation, data curation, and data annotation Interact directly with robotics and AV stakeholders to understand their technical needs and drive product development Design comprehensive monitoring and evaluation frameworks for robotics models and data quality Solving complex, late-stage industry challenges in concurrent and real-time robotic systems, with strict attention to timing constraints and data integrity. This often involves deep investigation, reviewing academic papers, and direct collaboration with robotics vendors Collaborate with ML engineers and researchers to bring robotics research into production Deliver features at high velocity while maintaining system reliability and performance Ideally, You Have: At least 6 years of high-proficiency software engineering experience, with a strong background in complex systems and the ability to independently research, analyze, and unblock hard technical problems. Strong programming skills in Python and TypeScript/Node.js for production systems Experience with React and m
Scale AI is seeking a highly skilled and motivated Software Engineer, ARC (Architecture, Reliability, & Compute) to join our dynamic Public Sector Engineering team. As a part of this team, you will define how the company ships software, establishing the patterns for deploying into complex government and high-security environments, rather than just running Terraform scripts. You will build and maintain internal CLIs/tools that standardize testing, deployment, environment management and are tools that engineering relies on to prevent downstream breakages. You will execute on automated deployment efforts to pay down tech debt, creating fully functional staging/testing environments, and defining the company's standard for safe deployments. You will: Design and implement secure scalable backend systems for Public Sector customers, leveraging Scale's modern and cloud-native AI infrastructure. Own services or systems and define their long-term health goals, while also improving the health of surrounding components. Re-architect the stack to run in compliant or restrictive environments. This requires designing swappable components (auth, storage, logging) to meet government/security mandates without breaking the product. Collaborate with cross-functional teams to define and execute the vision for backend solutions, ensuring they meet the unique needs of government agencies operating in secure environments. Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions. Contribute to the platform roadmap and product strategy for Scale AI's Public Sector business, playing a key role in shaping the future direction of our offerings. Must have: At least an active secret clearance and the ability & willingness to up level to TS/SCI with CI Poly. This is a requirement and candidates will not be considered who do not hold at least a secret clearance Ideally you'd have: Full Stack Development: Prof
#Team Nextdoor Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 350,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com . Meet Your Future Neighbors As a Software Engineer at Nextdoor, you’ll work across multiple phases of software development life cycle within a project to design, implement, and maintain the core backend systems that power the Company’s feed infrastructure. At Nextdoor, we operate in an AI-first environment and expect every team member to actively use AI tools as part of their workflow. We aren't looking for prompt engineers; we’re looking for people who use tools like Claude, Gemini, ChatGPT, and Glean to challenge their own thinking and take full ownership of AI-assisted outputs. We also offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The hiring team will go over these expectations with you if you are being considered for a role near one of our offices in San Francisco, Los Angeles, Chicago, Dallas, New York, and London. The Impact You’ll Make If you want the challenge of fast-paced growth, the satisfaction of seeing your design work come to life, and the pride in helping grow a world-class design team, this is the place for you. Your responsibilities will include: You’ll actively collaborate with product managers, frontend engineers, data scientists, and other backend engineers to understand the needs of the users and define the technical requirements for new features, improvements, and bug fixes You’ll monitor the performance of the feed infrastructure to identify bottlenecks and resolve issues in a timely manner
About the Team DoorDash’s GenAI Platform team sits within Machine Learning Platform and builds the shared infrastructure that helps DoorDash, Wolt, and Deliveroo teams safely bring GenAI-powered products, agents, automation, and personalization to production. Our mission is to increase the velocity of business impact from GenAI. A central pillar of that work is our evaluation platform — the unified evals backbone that lets teams measure, trace, and trust the quality of LLM and agent systems across the company, powering trace/score ingestion, LLM-as-judge workflows, agent simulations, and LLM observability for the tens of millions of daily requests flowing through our LLM Gateway. We also own core platform surfaces including the Agent Gateway, open-weights model serving and batch inference, guardrails, and cost attribution. About the Role You will join a small, high-leverage team building production infrastructure for Generative AI at DoorDash, with a primary focus on our evals and LLM observability platform: the systems that let teams evaluate, trace, and continuously improve the quality of LLM and agent products. You’ll work across evaluation frameworks and SDKs, OpenTelemetry-based trace/score ingestion, LLM-as-judge and offline/online eval pipelines, agent simulations, data pipelines, backend services, and observability. This role is ideal for an engineer who enjoys building reliable measurement and quality primitives in a fast-moving technical area where product needs, model capabilities, vendor ecosystems, and evaluation methodologies are evolving quickly. You’re excited about this opportunity because you will… Build the infrastructure that helps DoorDash teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company. Work on our unified evals platform — evaluation SDKs, OpenTelemetry trace/score ingestion, LLM-as-judge, offline and online eval pipelines, and agent simulations — alongside the LLM Gatew
At FourKites we have the opportunity to tackle complex challenges with real-world impacts. Whether it's medical supplies from Cardinal Health or groceries for Walmart, the FourKites platform helps customers operate global supply chains that are efficient, agile and sustainable. Join a team of curious problem solvers that celebrates differences, leads with empathy and values inclusivity. As a Senior AI Engineer, you'll join a 10-person team focused on data integrations (shippers and carriers moving in and out of the FourKites ecosystem) and our active AI agent workstreams — including a support automation agent handling 60-70% of customer tickets, a voice agent that calls carriers to gather and update information, and an end-to-end carrier onboarding agent (email + voice). You'll work on features end to end (~75-80% backend, ~20-25% frontend) using Python, Java/GoLang, agentic frameworks like LangGraph, React, Redis and PostgreSQL. You'll develop products that change the logistics landscape for some of the biggest corporations in the world, and work closely with our US team and customers to shape the future of the industry. What you’ll be doing: Design, build, and productionize AI agents/workflows (e.g., support automation, voice, and onboarding agents) using agentic frameworks such as LangGraph Develop, test, and maintain backend applications in Python and Java or GoLang Write clean, efficient, and well-documented code across the full SDLC — development, QA, and release Design and implement data models and database schemas Collaborate with the frontend team to integrate the backend with the user interface Perform code reviews and ensure code quality standards are met Troubleshoot and debug applications, including AI agent workflows in production Work with the DevOps team to deploy and manage applications in production (Kubernetes) Continuously learn and stay up to date with new technologies and industry trends, particularly in the AI/agentic space About the team: Our
Overview: Guidepoint seeks an experienced Data/AI Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s Next-Gen research enablement platform and data products. This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems, including large language model (LLM) applications and research agents, while ensuring the integration of responsible AI and best-in-class MLOps. The Senior AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s products. Guidepoint’s Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services. This is a hybrid position based in Toronto. What You'll Do: Architect and Build Production Systems: Design, build, and operate scalable, low-latency backend services and APIs that serve Generative AI features, from retrieval-augmented generation (RAG) pipelines to complex agentic systems. Own the AI Application Lifecycle: Own the end-to-end lifecycle of AI-powered applications, including system design, development, deployment (CI/CD), monitoring, and optimization
Overview: Guidepoint seeks an experienced AI Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s Next-Gen research enablement platform and data products. This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems, including large language model (LLM) applications and research agents, while ensuring the integration of responsible AI and best-in-class MLOps. The AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s products. Guidepoint’s Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services. This is a hybrid position based in Toronto. What You'll Do: Architect and Build Production Systems: Design, build, and operate scalable, low-latency backend services and APIs that serve Generative AI features, from retrieval-augmented generation (RAG) pipelines to complex agentic systems. Own the AI Application Lifecycle: Own the end-to-end lifecycle of AI-powered applications, including system design, development, deployment (CI/CD), monitoring, and optimization in production
EXPERIÊNCIA Solida experiencia de atuação na area ESCOLARIDADE Curso de graduação de nível superior em Administração (CBO 2521-05), Engenharia (CBO 214), Contabilidade (CBO 2522-10), Direito (CBO 2410), Economia (CBO 2512-05), Análise de Tecnologia da Informação (CBO 2124), ou Administrador de Tecnologia da Informação (CBO 2123) ou outras áreas correlatas à especialidade desde que validada pela gestão contratual da Petrobras. Conhecimento específico: Pós-Graduação com carga horária mínima de 360 horas de acordo com os subeixos de atuação, a ser definido . Backend Python 3.x avançado Django 4.x e Django REST Framework - experiência sólida PostgreSQL - otimização de queries e modelagem de dados Infraestrutura Linux (ambiente de desenvolvimento e produção) Git e fluxos de trabalho com branches Qualidade e Testes pytest e coverage para testes automatizados Code review e análise estática de código Certificação (no mínimo 1 delas): As certificações serão exigidas de acordo com a necessidade identificada CPC-A, CIA, SiAC, ISO9001 ou CertIFR ou Certificação PMI-ACP, CBPP, BPM ou Lean 6-Sigma (Black Belt) ou Certificação PMP ou PMI-ACP, Professional Scrum Master (PSM), Team Kanban Practitioner (TKP), Lean 6-Sigma (Black Belt) ou Ceritificação Oficial SAFe®. CONHECIMENTOS Desenvolver, manter e evoluir dashboards e painéis em Power BI, com foco em indicadores táticooperacionais, estratégicos e de gestão da rotina; Estruturar modelagem de dados, garantindo consistência, performance, governança e facilidade de manutenção; Criar e manter fluxos de automação no Power Automate, incluindo processos complexos com múltiplas etapas de aprovação, integrações com SharePoint, Teams e outras ferramentas corporativas; Desenvolver e evoluir aplicativos em Power Apps, observando boas práticas de arquitetura, versionamento, ambientes (DEV/TEST/PROD) e uso de Solutions; Atuar na sustentação e melhoria contínua de aplicações já exis
EXPERIÊNCIA Extensa experiencia de atuação na area ESCOLARIDADE Curso de graduação de nível superior em Administração (CBO 2521-05), Engenharia (CBO 214), Contabilidade (CBO 2522-10), Direito (CBO 2410), Economia (CBO 2512-05), Análise de Tecnologia da Informação (CBO 2124), ou Administrador de Tecnologia da Informação (CBO 2123) ou outras áreas correlatas à especialidade desde que validada pela gestão contratual da Petrobras. Conhecimento específico: Pós-Graduação com carga horária mínima de 360 horas de acordo com os subeixos de atuação, a ser definido . Backend Python 3.x avançado Django 4.x e Django REST Framework - experiência sólida PostgreSQL - otimização de queries e modelagem de dados Infraestrutura Linux (ambiente de desenvolvimento e produção) Git e fluxos de trabalho com branches Qualidade e Testes pytest e coverage para testes automatizados Code review e análise estática de código Certificação (no mínimo 1 delas): As certificações serão exigidas de acordo com a necessidade identificada CPC-A, CIA, SiAC, ISO9001 ou CertIFR ou Certificação PMI-ACP, CBPP, BPM ou Lean 6-Sigma (Black Belt) ou Certificação PMP ou PMI-ACP, Professional Scrum Master (PSM), Team Kanban Practitioner (TKP), Lean 6-Sigma (Black Belt) ou Ceritificação Oficial SAFe®. CONHECIMENTOS Desenvolver, manter e evoluir dashboards e painéis em Power BI, com foco em indicadores táticooperacionais, estratégicos e de gestão da rotina; Estruturar modelagem de dados, garantindo consistência, performance, governança e facilidade de manutenção; Criar e manter fluxos de automação no Power Automate, incluindo processos complexos com múltiplas etapas de aprovação, integrações com SharePoint, Teams e outras ferramentas corporativas; Desenvolver e evoluir aplicativos em Power Apps, observando boas práticas de arquitetura, versionamento, ambientes (DEV/TEST/PROD) e uso de Solutions; Atuar na sustentação e melhoria contínua de aplicações já exi
CAPCO POLAND We offer a flexible collaboration model based on a B2B contract. At Capco Poland, we're not just another consultancy – we're the spark behind digital transformation in the financial world. As a global leader in technology and management consulting, we help clients tackle complex challenges across banking, payments, capital markets, wealth, and asset management. Engagement Overview As a GenAI Developer, you will provide services related to the design, development, and deployment of scalable AI-powered applications using Large Language Models. Collaborating with cross-functional Agile teams, you will deliver production-ready solutions integrated into enterprise environments, helping clients unlock value from Generative AI. This engagement is well suited to professionals passionate about GenAI who enjoy combining strong backend and cloud expertise with modern AI capabilities. What You’ll Do Design, build, and deploy AI applications leveraging LLMs Develop scalable solutions using GCP services (Vertex AI, BigQuery, Cloud Run / Functions) Integrate LLM APIs (e.g. OpenAI, Vertex AI) into enterprise systems Design and implement RAG architectures Apply prompt engineering techniques to optimize model performance Build and maintain REST APIs and microservices Collaborate with cross-functional teams including data, backend, and business stakeholders Deliver high-quality solutions in agile, client-facing environments What We’re Looking For 3–6 years of experience in software development Strong hands-on experience with Python Experience with Google Cloud Platform (Vertex AI, BigQuery, Cloud Run / Functions) Practical experience working with LLM APIs (OpenAI, Vertex AI, etc.) Understanding of prompt engineering and RAG architectures Experience building REST APIs and microservices Strong communication skills and ability to work in a consulting environment Nice to Have Experience with LangChain or LlamaIndex Knowledge of embeddings and vector searc
Job Title: Full Stack Software Development Engineer II (SDE II) Team: Product Engineering Location: Bangalore, India Employment Type: Full-time About the Role As a Full Stack SDE II in Sigmoid's Product Engineering team, you will take ownership of building scalable, reliable, and user-centric web applications. You will collaborate closely with product managers, designers, and system architects to drive features from design to deployment, ensuring robust frontend performance, clean backend services, and efficient database architectures. Key Responsibilities Full Stack Development Design and build responsive, high-performance web interfaces using React, TypeScript, Tailwind CSS, and Shadcn UI, backed by reliable API services using Node.js or Python (FastAPI). Database & API Design Model, query, and optimize relational data structures in PostgreSQL. Design, build, and maintain clean RESTful APIs and microservices. Code Quality & Best Practices Apply SOLID principles, basic design patterns, and clean code principles to write maintainable, scalable, and self-documenting code. Testing & Quality Assurance Implement comprehensive test suites using Jest, React Testing Library, or backend testing frameworks (e.g., PyTest) to maintain high code coverage and prevent regressions. Agile Execution Actively participate in Agile ceremonies (sprints, stand-ups, retrospectives, and planning) to deliver quality code incrementally. Collaboration & Mentorship Partner with cross-functional teams and mentor junior engineers through constructive code reviews and technical guidance. Requirements & Qualifications Technical Skills Frontend 3–5 years of hands-on experience with React, TypeScript, Tailwind CSS, and modern UI component libraries like Shadcn UI. State & Data Fetching Experience with modern client-side state management and data-fetching libraries (TanStack Query, Zustand, or Redux Toolkit). Backend Strong expertise in server-side development using Node.js or
About the Team The Ona team at OpenAI is helping build the software factory for the enterprise. We build infrastructure that enables AI agents to work in secure, customer-controlled cloud environments, with the context, tools, and controls they need to make progress across the software lifecycle—beyond a single developer’s laptop or active session. Our focus is helping enterprises move from experimenting with agents to using them reliably in production. That means solving challenging problems in cloud environments, orchestration, security, and collaboration, while making the experience straightforward for the people directing and reviewing the work. We’re a team that values initiative, close relationships with customers, and exceptional engineering craft. We take ownership, learn quickly, and communicate directly and kindly. About the Role We’re hiring backend-focused Product Engineers across our platform and security product teams. You’ll build infrastructure and customer-facing workflows that let developers and AI agents work reliably in parallel. You’ll work primarily in Go on APIs, complex networking, development environments, and orchestration for long-running tasks. You’ll own outcomes from understanding a user’s problem and choosing an approach through shipping, operating, and improving the solution, working closely with frontend, infrastructure, and security engineers. In this role, you will: Work directly with customers to build developer and security workflows, from getting a project running to investigating findings, reviewing agent-generated changes, and verifying fixes. Build Go services and APIs for provisioning cloud environments, running agents in customer infrastructure, and integrating with source control, CI, and other developer tools. Design reliable orchestration for long-running, parallel work, including durable state, retries, cancellation, and recovery. Build security into execution workflows through clear permissions, credential handling, is
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