Forward Deployed Ai Engineer Jobs

About the role As a Forward Deployed Engineer (FDE) focused on Inference & Post-Training, you will be a hands-on technical partner to our most strategic customers — production AI teams looking to leverage high quality models and do inference at scale. For us, FDE is not a replacement for a Solutions Architect; you will partner with our SAs as a deep-domain specialist in inference optimization, fine-tuning pipelines, and production deployment. As key contributors to both the CX, Engineering, and Sales organizations, FDEs add tremendous value by ensuring we can meet the requirements of our most complex POCs, facilitate successful platform adoption, and guide tailored optimization efforts — directly impacting customer success, company growth, and the hardening of our core platform. Must be a permanent resident or citizen of Singapore. Responsibilities Inference Engine Optimization: Select, configure, and optimize inference engine based on hardware, model architecture, and workload profile Configuration & Performance Tuning: Develop configuration updates to win critical POCs, benchmarks, and optimize customer deployments; tune KV cache, apply speculative decoding, determine optimal tensor parallelism, and determine quantization strategy to hit throughput and latency targets. Post-Training & Fine-Tuning: Drive hands-on RL training runs and optimize system design; guide customers through LoRA, SFT, DPO, RLHF, and GRPO pipelines from experimentation through production. Strategic Customer Alignment: Act as the primary technical point of contact for aligned strategic accounts — monitoring and optimizing endpoint configurations, helping customers get the most out of the platform, and collaborating to ensure we hit critical milestones. Opinionated Onboarding: Establish direct alignment with strategic customers at onboarding; ensure the right inference and post-training configurations are in place from day one to improve time-to-value. Product Feedback Loop: D

Scale’s rapidly growing International Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of: Creating custom AI applications that will impact millions of citizens Generating high-quality training data for custom LLMs Upskilling and advisory services to spread the impact of AI As a Full Stack Software Engineer (Forward Deployed), you’ll collaborate directly with public sector counterparts to quickly build full-stack, AI applications, to solve their most pressing challenges and achieve meaningful impact for citizens. At Scale, we’re not just building AI solutions—we’re enabling the public sector to transform their operations and better serve citizens through cutting-edge technology. If you’re ready to shape the future of AI in the public sector and be a founding member of our team, we’d love to hear from you. You will: Serve as the lead technical strategist for public sector engagements, converting ambiguous mission requirements into robust architectural roadmaps and guiding onsite implementation Architect the fundamental frameworks for production-grade AI applications, setting the gold standard for how interactive UIs, backend systems, and AI models are integrated at scale to deliver reliable outcomes. Guide the evolution of cloud infrastructure, ensuring security, global scalability, and long-term system integrity across all environments. Direct the development of core platforms and shared services, ensuring they solve cross-cutting needs for diverse global client use cases. Partner with cross-functional leadership to steer the technical roadmap, mentoring senior and junior staff and ensuring all products align with a cohesive, future-proof technical architecture. Bridge the gap between the field and the core platform by turning real-world client lessons into the reusable patterns that power the entire engineering team. Ideally you’d have: Masters or Phd in Computer Science or eq

Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of: Creating custom AI applications that will impact millions of citizens Generating high-quality training data for custom LLMs Upskilling and advisory services to spread the impact of AI As a Full Stack Software Engineer (Forward Deployed), you’ll collaborate directly with public sector counterparts to quickly build full-stack, AI applications, to solve their most pressing challenges and achieve meaningful impact for citizens. At Scale, we’re not just building AI solutions—we’re enabling the public sector to transform their operations and better serve citizens through cutting-edge technology. If you’re ready to shape the future of AI in the public sector and be a founding member of our team, we’d love to hear from you. You will: Partner with public sector clients to scope, collect feedback and implement solutions for complex problems, including spending up to two weeks per month in client offices for feedback and delivery. Architect production-grade applications that integrate AI models with full-stack frameworks, managing everything from interactive UIs to backend APIs and systems. Deploy and manage infrastructure within cloud environments, ensuring the highest levels of system integrity, security, scalability, and long-term reliability. Contribute to core platform features designed to be reused across diverse international client use cases. Partner with design, product, and data teams to build robust applications aligned with the broader technical architecture. Ideally you’d have: Bachelor’s degree in Computer Science or a related quantitative field 5+ years of post-graduation, full-stack engineering experience with demonstrated proficiency in React (required), TypeScript, Next.js, Python, Node.js, PostgreSQL or MongoDB plus hands-on experience with Docker, Kubernetes, and Azure

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. About Okta for AI Agents Okta secures access for 20,000 organizations and billions of users. Okta for AI Agents extends that work to the agentic shift. Deploying an AI agent is not like deploying traditional software. You are putting professional work output into production, and it needs deep integration, continuous tuning, and change management. Every agent needs an identity, a scope, an audit trail, and a way to be shut down when it goes wrong. Most enterprises have not built this yet. We are. We hire builders who see the cracks in enterprise agent identity that everyone else has learned to live with. The Role You are the most senior technical field authority for agent identity at Okta. Where a Senior FDE owns the outcome inside one account, you own the patterns that every account and every FDE inherits. You take the hardest and most strategic deployments yourself, set the reference architecture the team builds from, and turn what the field learns into the direction the product takes. You still write code. You also multiply the people around you, and you are the person product and engineering leadership call when an agent identity problem has no precedent. Responsibilities Own the reference architecture. Define the canonical agent identity, delegation, audit, and kill-switch patterns that Senior FDEs deploy across the portfolio, and keep them current as the standards and the product move. Lead the hardest accounts. Personally own the most strategic, regul

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Principal Forward Deployed Engineer, Okta for AI Agents About Okta for AI Agents Okta secures access for 20,000 organizations and billions of users. Okta for AI Agents extends that work to the agentic shift. Deploying an AI agent is not like deploying traditional software. You are putting professional work output into production, and it needs deep integration, continuous tuning, and change management. Every agent needs an identity, a scope, an audit trail, and a way to be shut down when it goes wrong. Most enterprises have not built this yet. We are. We hire builders who see the cracks in enterprise agent identity that everyone else has learned to live with. The Role You embed inside four to five of Okta’s most strategic enterprise customers as their dedicated technical partner for agent identity. You sit alongside their identity, platform, and security engineering teams, develop sample and bespoke code, and own the technical outcome from prototype through production. You are a builder-consultant. You go past architecture diagrams to code, debug, and ship bespoke agent identity solutions inside the customer’s environment. You ship secure agents faster for the customer, and you feed real field insight back to Okta product engineering. Responsibilities Become the customer’s trusted technical voice on agent security. Sit in their standups, design reviews, and incident reviews. Earn a seat on their architecture review board and security council for agent risk d

We are looking for a deeply technical, customer-facing Forward Deployed Engineer to help product development organizations deploy Command - a new offering from Asana. As we incubate new motions and capabilities on Command, we need engineers who can work directly with customers, move quickly from insight to implementation, and bring real-world learning back into the product. This role is based in our San Francisco or New York City office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Collaborate with Engineering leaders, platform teams, administrators, and hands-on builders to connect Command to the systems where work already happens Establish the technical and operational foundations for adoption and help teams develop more effective ways of planning, building, shipping, and learning Move between cloud infrastructure, integrations, workflow design, automation, product enablement, and engineering coaching Work directly in customer environments — configuring secure access to source-control, CI/CD, ticketing, and identity systems, or pairing with engineering teams to design release workflows and help leaders clarify the context their agents and teams need to make good decisions Write production-quality code when needed and turn customer-specific solutions into reusable product capabilities Leave customers with more than a working deployment — leave them with a stronger system for building software About you 6+ years of experience in software engineering, forward deployed engineering, customer engineering, solutions engineering, implementation engineering, or a similar technical customer-facing role Strong coding and systems-thi

We are looking for a deeply technical, customer-facing Forward Deployed Engineer to help product development organizations deploy Command - a new offering from Asana. As we incubate new motions and capabilities on Command, we need engineers who can work directly with customers, move quickly from insight to implementation, and bring real-world learning back into the product. This role is based in our San Francisco or New York City office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Collaborate with Engineering leaders, platform teams, administrators, and hands-on builders to connect Command to the systems where work already happens Establish the technical and operational foundations for adoption and help teams develop more effective ways of planning, building, shipping, and learning Move between cloud infrastructure, integrations, workflow design, automation, product enablement, and engineering coaching Work directly in customer environments — configuring secure access to source-control, CI/CD, ticketing, and identity systems, or pairing with engineering teams to design release workflows and help leaders clarify the context their agents and teams need to make good decisions Write production-quality code when needed and turn customer-specific solutions into reusable product capabilities Leave customers with more than a working deployment — leave them with a stronger system for building software About you 6+ years of experience in software engineering, forward deployed engineering, customer engineering, solutions engineering, implementation engineering, or a similar technical customer-facing role Strong coding and systems-thi

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you'll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads — LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more. You're helping teams reach outcomes most engineers can't on their own. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and optimize production AI workloads

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for Forward Deployed Engineers on our engineering team who want to work at the intersection of deep infrastructure work and direct customer impact. As an FDE, you'll partner with leading AI companies and foundation labs on cloud architecture, networking, storage, containerization, sandboxing, and more — helping them design and ship production infrastructure on Modal's platform. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the infrastructure stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and deploy massive-scale production workloads on Modal Lead technical discovery and architect

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: Modal is seeking an experienced Forward Deployed Engineer (FDE) to partner with our sales team and drive technical sales success. As an FDE, you will be the technical voice in our sales process, working directly with Account Executives to help enterprise customers understand how Modal can transform their AI/ML infrastructure. You will: Partner with Account Executives to identify, qualify, and close strategic enterprise opportunities Lead technical discovery sessions with prospective customers to understand their current infrastructure, pain points, and requirements Design and present compelling technical solutions that demonstrate how Modal addresses customer needs Architect migration paths from existing cloud infrastructure (AWS, GCP, Azure) to Modal's serverless platform Conduct technical demos, experiments, and proof-of-concepts that showcase Modal's capabilitie

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you'll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads — LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more. You're helping teams reach outcomes most engineers can't on their own. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and optimize production AI workloads

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams. Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers. What's the opportunity? Over the past twelve months, we’ve seen rapidly growing demand for Software Engineers who thrive at the intersection of deep technical work, customer impact, and product strategy. As Fin's AI Agent for Customer Service, Fin, becomes mission-critical for our most strategic customers, we’re building a team of Forward Deployed Software Engineers to help bridge the gap between customer needs and product innovation. As a Forward Deployed Software Engineer, you’ll work hands-on with some of Fin's most strategic customers, partnering closely with our R&D and Go-to-Market teams to design and deliver high-impact solutions. You’ll go beyond implementation — helping shape product direction, influencing roadmap decisions, and ensuring Fin delivers real, measurable business outcomes in complex, real-world environments. If you’re excited by ownership, creativity, and solving ambiguous problems, and you want to work at the frontier of applied AI while collaborating with world

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams. Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers. What's the opportunity? Over the past twelve months, we’ve seen rapidly growing demand for Software Engineers who thrive at the intersection of deep technical work, customer impact, and product strategy. As Fin's AI Agent for Customer Service, Fin, becomes mission-critical for our most strategic customers, we’re building a team of Forward Deployed Software Engineers to help bridge the gap between customer needs and product innovation. As a Forward Deployed Software Engineer, you’ll work hands-on with some of Fin's most strategic customers, partnering closely with our R&D and Go-to-Market teams to design and deliver high-impact solutions. You’ll go beyond implementation — helping shape product direction, influencing roadmap decisions, and ensuring Fin delivers real, measurable business outcomes in complex, real-world environments. If you’re excited by ownership, creativity, and solving ambiguous problems, and you want to work at the frontier of applied AI while collaborating with world

About the team OpenAI’s Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development – working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project management expertise, extreme ownership of outcomes, and an ability to immerse in customer workflows and partner with customer teams to solve complex engineering problems at pace. This role is based in San Francisco. W

About the team OpenAI’s Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development – working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project management expertise, extreme ownership of outcomes, and an ability to immerse in customer workflows and partner with customer teams to solve complex engineering problems at pace. This role is based in NYC. We use a hy