Software Reliability Engineer Jobs

A CAREER WITH POINT72’S TECHNOLOGY TEAM As Point72 reimagines the future of investing, our technology group is constantly improving our company’s technology infrastructure, positioning us at the forefront of a rapidly evolving technology landscape. We encourage professional development to ensure you bring innovative ideas to our products while satisfying your own intellectual curiosity. The Back Office Technology Team supports trade processing, position keeping, clearing/settlement, fund accounting, trade reconciliation and prime broker integrations. The team partners with Middle and Back Office business users to customize and implement solutions supporting trade processing and new business developments. WHAT YOU’LL DO We are looking for an experienced professional to work as part of the Back Office Technology team. In addition to tactical development, you will be responsible for delivering and creating programs to modernize and scale the platform through technology upgrades, cloud technology adoption, and re-architecting business processes. You will work in the Back Office Technology team with world class engineers, developing high-capacity integrations and development capabilities with in-house and vendor build applications, implementing new financial products, managing internal and prime broker data, and developing the data warehouse of the future to support growing business. This position assumes close interaction with business and opportunity to build a high-demanding domain knowledge in post-trade flow. Build software applications and deliver software enhancements and projects supporting fund accounting and trade processing technology. Work closely with business stakeholders to develop software solutions using test-driven and agile software development methodologies. Be responsible for system upgrades and features supporting resiliency and capacity improvements, automation and controls, and integration with internal and external ven

JOB TITLE SOFTWARE ENGINEER, TECHNOLOGY A CAREER WITH POINT72'S TECHNOLOGY TEAM As Point72 reimagines the future of investing, our Technology team is constantly improving our company’s IT infrastructure, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts experimenting, discovering new ways to harness the power of open-source solutions, and embracing enterprise agile methodology. We encourage professional development to ensure you bring innovative ideas to our products while satisfying your own intellectual curiosity. WHAT YOU'LL DO We are looking for an experienced professional to work as part of the Finance Technology team. In addition to tactical development, you will be responsible for delivering and creating programs to modernize and scale the platform through technology upgrades, cloud technology adoption, and re-architecting business processes. You will work alongside world-class engineers, partnering directly with Finance stakeholders to understand existing workflows and deliver scalable replacements. This position offers deep domain exposure across FP&A, investor reporting, and compensation, and contributes to the modernization roadmap. Specifically, you will: Build software applications and deliver software enhancements and projects supporting finance and investor processing. Work closely with business stakeholders to develop software solutions using test-driven and agile software development methodologies. Be responsible for system upgrades and features supporting resiliency and capacity improvements, automation and controls, and integration with internal and external vendors and services. Contributing to architecture of core platforms and accelerating modernizing leveraging AI tools Work with DevOps teams to manage and resolve operational issues and leverage CI/CD platforms while following DevOps practices within the team and projects. Continuously improve the platforms using th

Role Overview You’ll be the Principal Software Engineer driving the next generation of a large-scale enterprise SaaS platform. In this role, you combine deep hands-on engineering with high-impact technical leadership, shaping how cloud-native and AI-enabled products are designed and built. You’ll design and deliver secure, scalable, serverless systems on AWS using TypeScript and Node.js, modernize critical platform components, and set the technical direction for multiple teams. You’ll also lead how AI capabilities are integrated across the product ecosystem, ensuring they are transparent, observable, and compliant. If you enjoy system-level thinking, complex distributed architectures, and mentoring senior engineers while still staying close to the code, this role gives you company-wide impact and the opportunity to define the long-term technical vision. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead the architecture and delivery of secure, scalable, serverless applications on AWS using TypeScript/Node.js. Define and evolve the platform architecture, driving modernization, performance, resilience, and maintainability. Design and operate distributed, event-driven systems using services like Lambda, DynamoDB, Aurora, S3, and EventBridge. Shape and implement AI-enabled solutions, embedding governance, observability, and responsible AI practices into the platform. Own Infrastructure as Code (e.g., Terraform, AWS CDK, CloudFormation) to reliably provision and manage cloud infrastructure. Mentor senior engineers, influence technical decisions across teams, and clearly communicate complex concepts to diverse stakeholders. These are the essentials you’ll need to get an interview Extensive experience (typically 12+ years) building secure, production-grade software systems. Proven track record architecting and delivering cloud-native, serverless applications on AWS. Strong expertise in Node.js, TypeScript, REST API design, and at leas

Platform administration isn't the part of the product anyone screenshots for a demo. Nobody's writing a blog post about your identity provisioning flow. But it's the thing every other team at Diligent quietly depends on more than any other dev team in the company and when it breaks, everyone notices immediately. If that kind of quiet, high-stakes ownership sounds appealing rather than thankless, keep reading. This role is for someone who wants real skin in the game: you build it, you ship it, you support it. We're a high-initiative team that improves things we see first and asks permission later, building secure, event-driven microservices in TypeScript on AWS, and treating infrastructure as code the same way we treat application code: with rigor, not as an afterthought. Here's a breakdown of what you'll do (not all of it, just the important stuff) Design and build secure, scalable full-stack services using AWS serverless tech (Lambda, SQS, API Gateway) — with real attention to event-driven patterns and observability, not just "does it work on my machine." Own your services in production. That means building good observability, keeping an eye on alerts, and responding to them before they become bigger problems. Build infrastructure as code with AWS CDK and push for CI/CD that ships safely and often — not "big bang" releases you have to pray over. Design RESTful APIs other teams will actually want to consume: clear contracts, sane versioning, no surprises. Write tests — unit, integration, end-to-end — as part of how you build, not a chore you do after. Show up to architecture discussions with opinions and documentation, not just vibes. Use AI tools to move faster on coding, debugging, testing, and research — but you're still the one who validates the output. These are the essentials you'll need to get an interview 2-3 years of professional software engineering experience in an agile, full-stack-focused environment. Solid full-stack fundamentals: request lifecycles, d

Position Overview: As a Software Engineer II at Diligent, you’ll take on a hands-on technical role in building secure, scalable, and high-performing serverless microservices using TypeScript on AWS. You’ll contribute meaningfully to our mission of making governance effortless for our customers, working in a team of passionate and talented individuals that owns its services end to end—from architecture and implementation to monitoring and continuous improvements. This role is ideal for a mid-level engineer who writes solid code and embraces AI-powered tools to work smarter and faster. You’ll help shape architectural discussions, and scale modern development practices, including responsible use of AI in workflows. Key Responsibilities Design and implement secure, scalable, high-performing, yet simple solutions using AWS Serverless technology. These solutions should strive to be event-driven, highly observable, with infrastructure as code, and tightly leveraging AWS’s ecosystem of services. Optimize your development and delivery experience in order to maximize your team’s productivity and deploy continuously to production. Work in a collaborative environment where you regularly pair, plan, and execute tasks as a team and maintain a healthy development flow by adhering to Agile processes and driving iterative enhancements. Use AI tools to accelerate coding, debugging, testing, research, and code reviews, always validating outputs and applying judgment. Required Experience/Skills 3–5 years of professional software engineering experience in an agile, fast-paced environment. AI Tooling & Practices: Uses AI to boost productivity, skilled in prompt engineering, and evaluates AI outputs responsibly (bias, cost, ethics). Familiar with core AI concepts (tokens, context length, embeddings, hallucinations), understands high-level LLM behavior, and recognizes safe vs. unsafe use cases (privacy, security, fairness). Cloud & infrastructure basics: Hands-on with AWS ser

This position is based in Vancouver, BC , within Diligent’s Technical Center of Excellence. We are currently hiring candidates who are based in or able to work from Vancouver . Software Engineer — Platform AI Service Levels: Software Engineer II Senior Software Engineer Staff Software Engineer Location: Vancouver Position Overview As a Software Engineer on Diligent's Platform AI team, you'll help design, build, and operate the core services that power AI-driven capabilities across Diligent's global product suite. You'll build secure, scalable, serverless services on AWS that translate AI research and models into commercial-quality, production-ready solutions — enabling customers to derive insights from their governance data. You'll work closely with AI researchers, product managers, and other engineering teams, owning your services end-to-end: architecture, implementation, deployment, and monitoring. The team operates with a strong AI-augmented engineering culture — using AI tools to accelerate coding, testing, debugging, and delivery — while applying sound judgment about when and how to apply them. Key Responsibilities Design and implement secure, scalable, fault-tolerant, high-performing solutions using AWS serverless technology — event-driven, highly observable, and built with infrastructure as code. Collaborate with AI researchers/engineers to translate AI and LLM capabilities into robust, production-grade services, and help other teams integrate them. Build and maintain the pipelines needed to deploy, monitor, and manage AI services at scale — observable, resilient, and cost-effective. Use AI-powered development tools (code assistants, test generation, architecture exploration) responsibly to accelerate delivery and improve quality, always validating outputs. Participate in architecture discussions and design reviews, and contribute to product design by understanding customer problems — especially where AI can offer a breakthrough solution. Work in

Here’s a summary of the role: Lead a strong engineering team, deliver software that matters, and help people do the best work of their careers. This is a hands-on team management role for someone who enjoys combining people leadership, technical fluency, and modern AI-enabled ways of working to build reliable products at scale. You’ll lead engineers building secure, scalable microservices and APIs using TypeScript and AWS. You’ll partner closely with Product, Security, DevOps, and peer engineering leaders to deliver roadmap outcomes, improve team effectiveness, and create an environment where engineers can grow, own their work, and build high-quality systems with confidence. Here’s a breakdown of what you’ll do, not all of it, just the important stuff: Lead, coach, and support a team of engineers, creating clarity around priorities, ownership, expectations, and growth goals. Partner with Product, Security, DevOps, and peer engineering leaders to plan and deliver roadmap commitments while balancing quality, pace, and sustainability. Create a healthy delivery environment by improving team processes, removing blockers, supporting planning and estimation, and reinforcing strong engineering practices. Maintain enough technical depth to guide design discussions, challenge risks, review trade-offs, and support the team in building secure and maintainable systems. Use AI tools and encourage responsible AI-assisted ways of working that improve productivity while protecting privacy, security, quality, and good judgment. Support hiring, feedback, performance conversations, and career development so the team continues to grow in capability and confidence. These are the essentials you’ll need to get an interview: 8 or more years of software engineering experience, including experience leading projects and supporting or managing engineers in an agile product environment. Experience managing teams that build cloud-native microservices in AWS. Strong people leadership skills, with

Here's a summary of the role: Do you love building scalable cloud platforms and solving complex engineering problems with modern technologies? As a Senior Software Engineer at Diligent, you'll design and deliver high-performing , serverless applications that power our global SaaS platform. You'll work extensively with TypeScript, Node.js, AWS, and event-driven microservices, owning services from design to deployment and production monitoring. This is an opportunity to influence technical decisions, mentor engineers, and explore how AI can transform software development and engineering productivity. If you're passionate about cloud-native architectures, distributed systems, and building software that scales to millions of users, we'd love to meet you. Here's a breakdown of what you'll do (not all of it, just the important stuff): Design and build scalable backend services and event-driven microservices using TypeScript and AWS. Develop secure APIs and integrations that power reporting, analytics, and dashboard experiences. Build and maintain serverless solutions using AWS services such as Lambda, EventBridge , SQS, and DynamoDB. Drive engineering excellence through testing, observability, automation, and production readiness practices. Contribute to infrastructure-as-code and CI/CD pipelines using AWS CDK and modern DevOps practices. Mentor engineers, participate in architecture discussions, and champion the use of AI tools to improve development efficiency. These are the essentials you'll need to get an interview: 6-8 years of professional software engineering experience. Strong experience with TypeScript, Node.js, and modern backend development patterns. Hands-on experience building cloud-native applications on AWS. Strong understanding of serverless architectures and event-driven microserv

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

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Identity Engineering team. In this role, you will help support the design and development of core software systems specifically focused on identity, access management, authorization, and authentication. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our identity infrastructure to ensure secure authentication and authorization across enterprise systems. Build software for authentication mechanisms such as Single Sign-On (SSO), Multi-Factor Authentication (MFA), and federated identity solutions (SAML, OAuth, OpenID Connect). Build software for authorization mechanisms such as Relation-based access control (ReBAC), Attribute-based access control (ABAC), Role-based access cont

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 is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Identity Engineering team. In this role, you will help support the design and development of core software systems specifically focused on identity, access management, authorization, and authentication. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our identity infrastructure to ensure secure authentication and authorization across enterprise systems. Build software for authentication mechanisms such as Single Sign-On (SSO), Multi-Factor Authentication (MFA), and federated identity solutions (SAML, OAuth, OpenID Connect). Build software for authorization mechanisms such as Relation-based access control (ReBAC), Attribute-based access control (ABAC), Role-based access cont

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. As our TT-Distributed Software Engineer, you will develop and optimize distributed software systems that power the most efficient and highest-performing AI and HPC clusters. In this role, you'll work on distributed programming across multiple nodes, utilizing systems programming, inter-node communication, and Tenstorrent’s scalable architectures to advance the state-of-the-art distributed inference and training infrastructure. This role is hybrid, based out of Santa Clara, CA; Austin, TX; or Toronto, ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Strong C or C++ engineer with solid foundations in systems programming, operating systems, and distributed systems principles. Enthusiastic about distributed computing, including IPC, socket programming, and cluster resource coordination. Comfortable reasoning about scalability, fault tolerance, and performance across multi-node environments. Curious and first-principles thinker who challenges conventional approaches to distributed system design. Motivated to grow into a deep technical expert in large-scale distributed AI infrastructure. What We Need Architect, implement, and optim