Lead the engineering foundation behind reliable, measurable, and scalable AI-powered features.
Build evaluation frameworks, observability tooling, and diagnostic infrastructure for AI agents in production.
Combine hands-on software engineering with technical leadership and people management.
The company builds AI-powered products with a focus on reliability, scalability, and evaluation infrastructure. It operates as a fully remote, globally distributed team with an ownership-oriented culture.
Lead the effort to make Runpod the fastest and most cost-efficient place for LLM inference, owning performance end to end.
Profile and diagnose performance bottlenecks across the serving stack, from scheduling to kernels, and implement fixes.
Work closely with product and infrastructure teams to shape how inference is offered, turning improvements into production-ready defaults.
Runpod is the AI Developer Cloud, providing a platform for over one million developers to experiment, train, fine-tune, deploy, and scale AI. We're a small, remote-first team that takes ownership seriously, moves fast, and has processed more than 20 billion inference requests.
Lead technical evaluations and proofs of concept for an enterprise AI coding platform in real customer environments.
Engage directly with CTOs, VPs of Engineering, and senior developers on AI agent architecture and integration.
Manage enterprise security and deployment reviews, troubleshoot integration issues, and feed customer insights into product.
The company is an enterprise AI coding platform provider helping engineering organizations accelerate development with AI agents and LLM infrastructure. It operates as a remote-first global team with a fast-paced, innovative culture focused on collaboration and rapid product iteration.
Build and operate production-grade agentic AI workflows for customer experience operations.
Develop MCP servers, secure integrations, and shared platform capabilities on AWS.
Establish evaluation, observability, and governance practices for reliable AI systems.
A technology company focused on integrating AI-powered workflows into customer experience operations. They foster a collaborative, inclusive remote culture emphasizing production-grade engineering, rapid prototyping, and mentorship.
Architect, build, and optimize high-performance production LLM systems while maintaining a strong personal technical presence on the team.
Spearhead strategic technological changes and champion code refactoring efforts to keep the core codebase cutting-edge and performant.
Lead technical story breakdowns, architectural design, and mentor engineers across the department.
Appian provides AI automation for mission-critical work, automating complex processes in large enterprises and governments. With over 25 years of experience, the company is known for its reliability and scale, and fosters an inclusive culture with employee-led affinity groups.
Build LLM-based agents on the platform's scaffolding, integrating tool calls, internal APIs, and guardrails.
Take agents to production on AWS with containers, CI/CD, secrets, permissions, and security controls.
Define and run evals, monitor with Langfuse, and document runbooks for independent operation.
Muttdata builds innovative Data Products and Machine Learning solutions to help companies solve complex business challenges. It is a fast-growing, remote-first startup that values collaboration, continuous learning, and a positive, ownership-driven culture.
Architect AI infrastructure including backend services, data pipelines, and orchestration workflows for LLMs.
Write production-grade, high-performance code for high-throughput AI workflows and data-driven systems.
Integrate foundational models, vector data stores, and cloud microservices into scalable platform components.
Korza builds AI infrastructure and products, specializing in LLM and agent-based systems. The company emphasizes cross-functional collaboration and rapid shipping of cutting-edge AI capabilities.
Design, build, and deploy production ML and LLM-based systems for enterprise clients.
Own technical delivery end-to-end from architecture to deployment and iteration.
Mentor and support other ML engineers through code reviews and technical guidance.
TensorOps is a boutique AI consultancy that designs and ships production-grade AI systems for enterprise clients. The company has shipped AI systems impacting 200M+ end users daily, partnered with 11 unicorns, and operates fully remotely with a supportive, fast-growing culture.
Lead client-facing engineering and solutioning from pre-sales through early delivery for enterprise AI platforms.
Architect and implement AI stacks, agentic solutions, and cloud-native platforms using Python, GenAI, and LLMs.
Drive AIOps, observability, and mission-critical platform transformation programs for regulated industries.
Global technology consulting and digital solutions company that enables enterprises to reimagine operations and drive measurable business impact. Its Enterprise AI business unit focuses on scaled, production-grade AI adoption and agentic platforms.
Lead the AI Platform team to build the technical rails for AI-native operations, including LLM gateway, agent framework, and evaluation infrastructure.
Drive the Velocity program to achieve true autonomy by optimizing product delivery cycle time with AI-written code and coverage gates.
Grow the platform org through a Director and principal engineers, holding the line on a single shared platform across all domains.
Engine is the all-in-one travel and spend management platform trusted by 38K+ businesses and 1.8M+ travelers. With 1,000+ employees, we are one of the fastest-growing companies in travel tech, recognized as a Best Place to Work and a leader in AI innovation.
Design, build and operate production AI agents, including an autonomous coding agent that works from Jira and Slack, opening PRs and fixing CI failures.
Build the retrieval and context layer behind our AI brain: embeddings, semantic search, knowledge-graph modeling, and integration with Snowflake and internal docs.
Harden agents against prompt injection and over-broad permissions, and drive cost and latency down using caching and structured outputs.
Weedmaps is a global leader in the cannabis industry, providing a platform for consumers and businesses. The company has a collaborative culture focused on innovation and community, serving the U.S. and worldwide.
Set the technical direction for AI engineering across the team: agent architecture patterns, evaluation methodology, deployment and monitoring strategies
Design the AI platform layer, including shared agent frameworks, tool integrations, and evaluation infrastructure
Work directly with clients on the most complex engagements, identifying new problem domains and ensuring production quality
Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. With over 1,500 firms in 60 countries managing nearly $10 trillion in assets, Addepar fosters a culture of ownership, collaboration, and innovation.
Design and build autonomous AI agents using modern agentic frameworks to analyze infrastructure and make intelligent decisions.
Develop and deploy ML models and MLOps pipelines that learn from infrastructure patterns to optimize resource policies and scaling.
Own AI systems end-to-end, from architecture to production, ensuring performance, reliability, and cost-effectiveness.
ScaleOps is redefining autonomous cloud and AI infrastructure by freeing DevOps teams from manual resource management, reducing cloud costs by up to 80%. Backed by over $210M from leading VCs, the company is trusted by Fortune 100 companies and fosters an innovative, mission-driven culture.
Build the component layer around our layout synthesis engine, including API contracts, services, and evaluation gates.
Turn model retraining into a one-command job with built-in benchmarks and readable results for the whole team.
Own latency and cost budgets for learned capabilities and partner with infrastructure engineers on MLOps and deployment.
Higharc is a VC-backed startup that is changing how new homes are designed and built using spatial AI and generative floor plan technology. The company is fully remote, has raised over $175M, and values flexibility, collaboration, and asynchronous deep work.
Own the build out of new agents, skills, and platform capability for teams across TLDR.
Build and deploy agents end to end, from design through implementation, evals, and rollout to internal users.
Partner with stakeholders across sales, editorial, and people ops to find where an LLM belongs in their process.
TLDR runs the largest network of tech newsletters in the world, with over 8 million subscribers covering startups, software engineering, AI, and more. Our 31-person full-time team is bootstrapped, profitable, and on track for $35M in revenue this year, with a culture of owning functions rather than slices.
Design, build, and ship custom internal AI tooling, agents, and workflows for autonomy and research.
Integrate and extend third-party AI tools and evaluate new AI models with structured pilots.
Partner with cross-functional teams to prototype solutions and drive adoption of AI tools.
Waabi is a leader in Physical AI, founded by AI visionary Raquel Urtasun. The company is growing quickly with offices in Toronto, San Francisco, Dallas, and Pittsburgh, and seeks diverse, innovative candidates.
Design, develop, and deploy multi-agent AI systems for reasoning and task execution.
Implement RAG pipelines and optimize model serving for low-latency inference.
Build observability frameworks and apply security techniques for robust AI behavior.
AB InBev is a leading global brewer and top consumer product company with over 500 beer brands. The Growth Group is an exceptional team focused on digital transformation and scaling growth opportunities.
Own end-to-end technical strategy for major areas of the Voyager SDK’s application layer, including model deployment and pipeline development.
Set technical direction for image processing, create reusable architectures, and partner with the compiler team to resolve compilation issues.
Represent the Applications team’s capabilities to business stakeholders, mentor engineers, and drive documentation standards.
Axelera AI is a deep-tech company creating a next-generation AI platform to advance humanity. With $450 million raised and 250+ employees including 60+ PhDs, they have a strong business pipeline exceeding $100 million and are committed to innovation.
Develop deep understanding of customer problems and map them to Cohere solutions as a trusted technical advisor.
Lead design and deployment of customer pilots, owning the technical narrative from discovery to business case.
Collaborate with Product and Engineering teams and partners to scale solutions and gather customer feedback.
Cohere is a leading security-first enterprise AI company building cutting-edge foundation AI models and products for real-world business problems. It is a global team of researchers, engineers, and designers headquartered in Toronto with offices worldwide, committed to driving AI adoption.
Develop and deploy cutting-edge AI/ML solutions to enhance the platform and improve student learning experiences.
Design, develop, and optimize LLM-powered agentic systems and APIs for real product use cases.
Collaborate with senior engineers and contribute to evaluation frameworks and MLOps pipelines.
Interview Kickstart specializes in interview preparation and career transitions into high-demand tech fields like AI, ML, and Data Science. Over 17,000 tech professionals have been guided by current and former hiring managers to land coveted positions at companies like Google and Amazon.