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We’re looking for a Software Engineer to help shape AI governance for developer tooling at Coder. This role sits on our AI Governance team, which builds and maintains two enterprise-grade components of Coder's AI governance stack. AI Gateway is a centralized LLM gateway that sits between coding agents and providers such as OpenAI or Anthropic, providing organizations with audit trails, token tracking, cost control, and centralized authentication. Agent Firewall wraps those agents with default-deny network policies, controlling which domains and methods they can reach inside workspaces. This team works across the full stack - from Go backend and React frontend, to integrating with LLM provider APIs. Day to day, you'll be shipping features, hardening security boundaries, collaborating with enterprise customers on real-world policy needs, and contributing to Coder's open-source ecosystem. What you'll do here Design and build product features that push the standard for remote development in self-hosted environments Create and improve upon popular open source projects that integrate with VS Code, JetBrains, and other developer tools Champion best practices to both internal team members and external contributors Collaborate with Product and Design teams at Coder, as well as with partners like JetBrains, to execute key product integrations Document the design, implementation, and operations of systems for knowledge sharing within the team Work alongside Customer Success teams to support Coder’s enterprise user base Work with cutting-edge AI technologies to create seamless, painless developer experiences Rapidly iterate from prototype to implementation in a highly adaptive, reactive team environment What we're looking for 3+ years of full-stack experience writing code in a professional setting, with 1+ year(s) writing Go (ideally in current or most recent position) Proficiency in building distributed systems in Go Excellent verbal and written communication skills Exceptiona

About the Team The Technical Success team is responsible for ensuring developers and enterprises are successful in building scalable production applications with the OpenAI API platform. We guide and support customers to achieve maximum benefits, value, and adoption from deploying our highly-capable models. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. About the Role We are looking for a technically savvy and business-minded AI Deployment Engineer to deeply partner with our most strategic and high-impact platform customers, guiding them through application ideation, development, delivery, and scale to accelerate and maximize the value of what they build with our platform. You will have the opportunity to work on the most novel and creative use cases being built on our API, serving as a critical partner for collecting and delivering high fidelity feedback to Product and Research teams. This role is based in Tokyo, Japan. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees In this role, you will: Deeply embed with our most strategic platform customers, serving as their technical thought partner in ideating and building novel applications on our API. Proactively provide guidance to our customers on how to maximize business impact from their applications, accelerating their time to value. Experiment and prototype solutions with and for your customers. Forge and manage relationships with our customers’ leadership and stakeholders to ensure their application’s successful deployment and scale. Contribute to our open-source developer and enterprise resources. Scale the AI Deployment Engineering function through sharing knowledge, codifying best practices, and publishing notebooks to our internal and external repositories. Validate, synthesize, and deliver high-signal feedback to the Product and Research teams. Use your expertise i

NK Securities Research is a leading financial firm that leverages cutting-edge technology and sophisticated algorithms to trade the financial markets. Founded in 2011, we have gained invaluable experience in the field of High-Frequency Trading (HFT) across different asset classes. Role Overview We’re looking for engineers who can take AI work beyond experiments and make it hold up in production. You’ll work closely with quant researchers and infra engineers to build AI systems that actually get used improving research speed and internal tooling without slowing down the core stack. We value engineers who think about trade-offs, test what they build, and care about how things run in production. What You’ll Build Production AI Ship models that meet defined latency and reliability expectation Add monitoring, rollback, and guardrails before anything goes live Optimise inference across CPU/GPU environments when it matters Integration into Real Systems Plug AI into data-heavy workflows without hurting performance Work within existing low-latency architecture instead of fighting it Profile and remove bottlenecks rather than guessing AI for Engineers & Researchers Build tools that genuinely speed up research and development Improve code understanding, review workflows, and internal knowledge retrieval Keep systems auditable and predictable LLM & Retrieval Systems Implement structured RAG and embedding pipelines with validation in place Create safe integration layers between models and internal systems Performance & Standards Track latency, drift, and stability — not just accuracy Build observability into everything you ship Help raise the bar for how AI is engineered here What We’re Looking For Strong Python fundamentals Clear thinking around system design and performance trade-offs Experience deploying AI systems in production (1–5 years is typical) Familiarity with transformers, embeddings, or LLM deployment Nice to have: Exposure to C++ / Rust / Go E

At Dscout, we’re building the most flexible and powerful UX research platform on the market—trusted by the world’s top brands in finance (JP Morgan Chase, Intuit, Charles Schwab, PayPal), healthcare (Aya, Headspace), consumer goods (Keen, Verizon, Target, Northface), and tech (Google, Amazon, Facebook, Meta, Spotify, AirBnB). Our tools help teams deeply understand the humans behind their products, so they can build better ones. We are expanding our smart and driven team and would love for you to join us. We're looking for an AI Product Manager who brings the full standard PM toolkit — user research, market and competitive analysis, roadmap and strategy, cross-functional delivery, and strong collaboration instincts - and applies it to products where the model underneath doesn't behave the same way twice. You have a real, hands-on feel for what different LLMs are actually good and bad at, and you use that to prototype ideas yourself, sometimes shipping small, production-quality AI features directly. You default to ownership: of the roadmap, of outcomes, of the quality bar that decides whether something's actually ready to ship, and of what an agent should be trusted to do on its own versus when a human needs to stay in the loop. That's because building AI-native products means quality is a distribution, not a pass/fail — a feature can work correctly most of the time and still need a real answer for the failure tail, since the underlying system is non-deterministic, not just complex. What you'll do Lead the roadmap and strategy for your product area, from problem discovery through delivery and post-launch iteration Lead the evaluation bar for the model-powered surfaces you're responsible for: define eval sets, identify failure modes, and know the rollback plan before a change ships Prototype product ideas directly using your own understanding of model strengths and weaknesses, and ship small, production-quality AI features yourself when that's the fastest path to

We're hiring an AI Support Engineer to work directly with the founder and build the systems that power customer support at Bolna. This isn't a traditional support role — you'll use AI to make support scale, and you'll partner closely with the business team on the customer conversations that matter most. What you'll do - Work directly with the founder to design and continuously improve how customer support runs at Bolna - Pull and collate data from Intercom to spot patterns, recurring issues, and gaps in how customers are being helped - Build AI-powered workflows that triage, answer, and resolve customer support queries with less manual effort - Design the systems and processes behind a streamlined, scalable support flow — from triage to escalation to resolution - Step in directly on critical customer support situations alongside the business team when it matters - Turn recurring support themes into feedback for product and engineering What we're looking for - 1–3 years of experience in a support, ops, or technical customer-facing role — ideally somewhere that rewarded building your own tools and process, not just following a playbook - Hands-on comfort with AI tools/workflows (prompting, automations, agent builders) — you don't need to be an ML engineer, but you should be someone who reaches for AI to solve a workflow problem - Experience with Intercom or a similar support/helpdesk tool - Sharp, structured communicator — equally comfortable writing to customers and to the founder - Comfortable with ambiguity — this role is being built as you build it Nice to have - Experience setting up support automations, chatbots, or AI agents in a real product company - Familiarity with SQL or basic scripting to pull/analyze support data - Startup experience, especially in a 0-to-1 function

About the Team The AI Deployment Engineering team is responsible for ensuring the safe and effective deployment of Generative AI applications for developers and enterprises. We act as a trusted advisor and thought partner for our customers, working to build an effective backlog of GenAI use cases for their industry and drive them to production through strong technical guidance. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. About the Role We are seeking a technically proficient, business-minded AI Deployment Engineer to help push the frontier of advanced AI with our strategic startup customers. You'll work with some of the most exciting AI startups in the world, guiding them through ideation, development, delivery, and scaling to accelerate and maximize the value of what they build on our platform. You will have the opportunity to work on the most novel and creative use cases being built on our API, serving as a critical partner in collecting and delivering high-fidelity product and model feedback internally. You will collaborate closely with Sales, Solutions Engineering, Applied Research, and Product teams, and you will report to the Startups Solutions Architecture Lead. This role is based in Tokyo. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Partner closely with strategic startup customers as their technical thought partner to build novel applications on our API, helping them rapidly move from ideation to scale. Provide proactive guidance to maximize business impact and accelerate application development. Experiment and prototype alongside customers, demonstrating practical use cases. Contribute to open-source resources and scale the function by sharing knowledge, codifying best practices, and publishing useful resources. Synthesize and deliver valuable feedback to the Product and Research

About the team The AI Deployment Engineering team ensures the safe and effective deployment of Generative AI applications for developers and enterprises. We serve as trusted technical advisors, helping customers and partners move from early experimentation to production-scale AI systems. As a Partner AI Deployment Engineer focused on AWS, you will operate at the center of one of our most strategic partnerships, driving joint customer success and enabling AWS and partner ecosystems to scale adoption of OpenAI-powered solutions. About the role We are looking for a highly experienced technical leader to serve as the primary technical counterpart to AWS field leadership (Solutions Architects, Specialists, and Partner teams). This role goes beyond individual deal support—you will shape strategy, define engagement models, and build repeatable systems that scale across AWS globally. You will work across pre- and post-sales, guiding complex enterprise customers from ideation to production while enabling AWS and partners to independently drive deployments. You will combine deep technical expertise, strong judgment, and ecosystem leadership to maximize impact across a portfolio of high-priority opportunities. This role is based in Bangalore . In this role, you will: Strategic AWS Engagement & Influence Serve as the senior technical counterpart to AWS field leadership, building trust and credibility across regions and teams. Influence joint account strategy and technical direction for high-priority opportunities. Shape how OpenAI engages with AWS by defining engagement models, prioritization frameworks, and best practices. Proactively identify and drive net-new opportunities and high-impact use cases across the AWS ecosystem. Complex Deal Leadership & Execution Lead technical strategy for large, ambiguous, and high-stakes enterprise engagements. Guide customers from early ideation through architecture design, prototyping, and production deployment. Act as a technical d

About the team The AI Deployment Engineering (ADE) team ensures the safe and effective deployment of Generative AI applications for developers and enterprises. We act as trusted advisors and technical partners to our customers, helping them build and execute their AI adoption strategy post-sale. Our mission is to develop a strong backlog of GenAI use cases tailored to each customer’s industry and to drive these initiatives from prototype to production through hands-on technical guidance and partnership. As a Partner ADE, you’ll support systems integrators and their most strategic customers transform their business through solutions such as customer service, automated content generation, and novel applications that make use of our newest, most exciting models. About the role We are looking for a driven solutions leader with a product mindset as the founding Partner ADE to own the technical engagement with our systems integrators (including GSIs, RSIs, and boutique SIs) and ensure their customers achieve tangible business value with GenAI. You will help partners identify high-value use cases and provide technical enablement through the implementation of AI solutions. Your efforts will accelerate partners’ time to unlock distribution and adoption, ensuring they deliver exceptional results for our joint customers while maintaining high-quality standards. You will collaborate closely with Sales, Solutions Engineering, Applied Research, and Product teams, and you will report to the Head of Solutions Architecture. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Deeply embed with GSIs, RSIs, and boutique SIs as the technical lead, serving as their technical thought partner to ideate and build novel applications on our API for their customers. Work with senior SI and customer stakeholders to identify the best applications of GenAI in their industry a

About the Team OpenAI’s HLS AI Success Engineering team partners with the world’s most ambitious healthcare and life sciences organizations to translate cutting edge AI into real patient outcomes. We guide customers from first deployment through scaled enterprise adoption. Our work spans technical integration and enablement, workflow transformation, and sustained program and product delivery. Our customers range from fast-growing healthcare and life sciences innovators to the world’s largest biopharma, medical technology, healthcare provider, payer, and research organizations. Every engagement is an opportunity to shape how AI accelerates scientific innovation, transforms healthcare delivery, and improves patient outcomes.This role sits at the center of our mission. About the Role The AI Success Engineer role is the primary post-sales point of contact for OpenAI’s most important customers. You are responsible for driving account health and adoption, ensuring technical readiness, identifying new use cases, and delivering measurable value to our customers with OpenAI’s ambitiously growing platform. This role blends technical depth, program management, customer advisory, and product influence. You will partner deeply with customer teams, map workflows, lead configuration, oversee deployment plans, and guide customers toward high impact use cases that showcase the full value of our platform. You will work closely with Sales, Solutions Architecture, Product, and Research to ensure the customer experience is connected and successful across every touchpoint. Success in this role means accelerating adoption, increasing customer activation depth, guiding strategic use cases that get to production, and helping customers demonstrate tangible impact. This role is based in San Francisco or NYC, with a hybrid schedule of 3 days per week in the office, or can be performed remotely from anywhere in the U.S. We also provide relocation support for new employees. In this role, you wil

About the Team OpenAI’s HLS AI Success Engineering team partners with the world’s most ambitious healthcare and life sciences organizations to translate cutting edge AI into real patient outcomes. We guide customers from first deployment through scaled enterprise adoption. Our work spans technical integration and enablement, workflow transformation, and sustained program and product delivery. Our customers range from fast-growing healthcare and life sciences innovators to the world’s largest biopharma, medical technology, healthcare provider, payer, and research organizations. Every engagement is an opportunity to shape how AI accelerates scientific innovation, transforms healthcare delivery, and improves patient outcomes.This role sits at the center of our mission. About the Role The AI Success Engineer role is the primary post-sales point of contact for OpenAI’s most important customers. You are responsible for driving account health and adoption, ensuring technical readiness, identifying new use cases, and delivering measurable value to our customers with OpenAI’s ambitiously growing platform. This role blends technical depth, program management, customer advisory, and product influence. You will partner deeply with customer teams, map workflows, lead configuration, oversee deployment plans, and guide customers toward high impact use cases that showcase the full value of our platform. You will work closely with Sales, Solutions Architecture, Product, and Research to ensure the customer experience is connected and successful across every touchpoint. Success in this role means accelerating adoption, increasing customer activation depth, guiding strategic use cases that get to production, and helping customers demonstrate tangible impact. This role is based in San Francisco or NYC, with a hybrid schedule of 3 days per week in the office, or can be performed remotely from anywhere in the U.S. We also provide relocation support for new employees. In this role, you wil

About Zinnov Zinnov is a global management consulting firm that helps organizations make decisions that actually get used — and deliver results that matter. For over two decades, we’ve partnered with leading enterprises, high-growth technology companies, and investors to answer some of the toughest questions they face: Where should we invest? How do we scale globally? What capabilities will win in the next decade? Our work shapes market entry strategies, global operating models, M&A decisions, and long-term growth bets. We’re known for being data-led, execution-focused, and outcome-driven — not opinion-heavy slideware. At Zinnov, how you work matters as much as what you deliver. We value independent thinking, crisp communication, and early ownership. With 450+ professionals across 10 global offices, we work across industries including Digital Services, ER&D, Enterprise Software, Semiconductors, Healthcare, BFSI, Automotive, Media & Telecom, and Private Equity. Zinnov isn’t for everyone. It’s for people who want steep learning curves, honest feedback, and the chance to see their work influence real business decisions — not just presentations. About the Role As an Agent / AI Engineer , you will build the AI layer of the GCC Intelligence Platform—the conversational agent users interact with. You will own grounding, retrieval, persona routing, session state, and permission-aware querying so the agent stays accurate, secure, and tenant-safe. What You’ll Do LLM & Agent Integration Integrate LLM APIs (e.g., AzureOpenAIor equivalent) for conversational workflows. • Build a grounding layer that anchors responses to real platform data (not model guesses). • Maintain prompt templates across multiple personas and use-cases. Retrieval, Permissions & Security Boundaries Implement intent classification and persona routing to the right KPI views. • Build the API

MeltPlan | Planning Engine for the Built Environment MeltPlan is building the “planning engine” for the $14 Tn construction industry, an AI system designed specifically to optimize decisions before construction begins. While design software optimizes use and aesthetics and construction software optimizes execution and control, MeltPlan is building the missing layer - software that optimizes decisions and tradeoffs upstream, before scope is locked, procurement begins, and change orders become inevitable. MeltPlan’s long-term goal is to help teams make construction “boring” by making planning more intense: surfacing constraints and tradeoffs early, aligning stakeholders before plans are frozen, and reducing the need for late-stage redlines, rework, and change orders. MeltPlan is founded by operators who have built at scale. Kanav previously co-founded Innovaccer, a $3Bn healthtech company focused on making US healthcare more affordable and accessible. He’s now applying that systems-level thinking to construction.He’s joined by Tanmaya Kala, former Project Executive at DPR Construction, who led large commercial, healthcare, and life sciences projects. We combine deep tech scale with real construction execution. What This Role Really Is We are looking for an AI Research Scientist – Computer Vision to enhance and manage the PlanGraph model, which transforms 2D drawings into structured graphical representations of building elements. The role involves solving downstream business use cases such as quantity takeoff, code compliance, value engineering, and constructability analysis.We are specifically looking for hands-on researchers with experience in solving real-world Computer Vision problems and building custom vision models, VLMs, or VLLMs for production-grade applications. What You’ll Do Build and optimize custom Computer Vision models, VLMs, and VLLMs for construction intelligence workflows. Solve downstream business use cases including quantity takeoff, code complianc

Razorpay is one of India’s leading full-stack financial technology companies, powering the way businesses move, manage, and grow money. Founded in 2014 by Harshil Mathur and Shashank Kumar with a simple vision - to simplify payments for Indian businesses - we’ve since grown into a fintech powerhouse driving India’s digital payment revolution. Razorpay powers millions of businesses with a smarter, scalable stack that goes beyond transactions to help them truly build and grow. From building AI-native agentic payments, to AI-assisted fraud detection and real-time risk intelligence to automated reconciliation, smart payouts, and predictive financial insights, we are embedding intelligence across our stack to make money movement faster, safer, and more efficient. In close collaboration with ecosystem partners - including banks, networks, regulators - we are pioneering industry-first solutions that are shaping the next era of fintech Across India, Singapore and Malaysia, our products span everything from seamless checkouts to payroll automation - powering a fintech ecosystem that’s redefining how money moves across Asia. Today, that ecosystem supports everyone from early-stage startups to some of India’s largest enterprises, enabling them to accept, process, and disburse payments at scale while expanding into new ways of managing money more efficiently. Our scale speaks volumes: Razorpay processes $180+ billion in annualized transactions, powering leading businesses like Airbnb, Facebook, WhatsApp, Airtel, CRED, BookmyShow, Zomato, Swiggy, Lenskart, Mirae Asset Capital markets, Indian Oil, National Pension Scheme - and over 100 of India’s unicorns. With strong roots in India and growing operations in Southeast Asia, we are shaping the next chapter of financial technology across the region. We are backed by global investors including GIC, Peak XV Partners (formerly Sequoia Capital India & SEA), Tiger Global, Ribbit Capital, Matrix Partners, MasterCard, and Salesforce V

AI/ML Dev - Chatbots • 8+ years of experience in Data/AI Projects • Understanding of end-to-end architecture for Generative AI solutions aligned with business goals. • Experience in Azure OpenAI integration (GPT models, embeddings) with prompt engineering and model tuning. • Programming experience in Python for AI project is a must • Designs scalable RAG systems using Azure AI Search, vector databases, and secure data pipelines. • Knowledge of MLOps and CI/CD workflows using Azure DevOps and automated testing frameworks. • Establishes Python coding standards, reviews code, and mentors development teams. • Knowledge of deployment and governance of AI applications across Azure infrastructure. • Work with cross function teams (IT/ Non IT) to help the development teams build the solutions faster and more efficiently.