Polar Operations LLC (dba IMC Markets) has multiple openings for Python Software Engineer (REQ#4461661101) in Chicago, IL and Brooklyn, NY.

Your Core Responsibilities

• Implement software features and components for IMC's trading systems (25%).
• Design software solutions independently and make architectural decisions (10%).
• Debug and fix software issues in trading systems (5%).
• Identify complex multi-component issues, perform root cause analysis, and implement preventative solutions (5%).
• Ensure code quality and system reliability through comprehensive automated testing (10%).
• Contribute to the automated testing framework, own critical trading system components, and ensure reliability, performance, and scalability across regions (5%).
• Participate in code reviews (10%).
• Monitor system performance and trading operations (5%).
• Collaborate with traders and other teams to understand requirements and deliver solutions (10%).
• Participate in planning, estimate complexity of tasks, and help balance technical debt with feature development (5%).
• Mentor and guide junior developers and interns, helping them understand IMC's systems and development practices (10%).

Partial telecommuting permitted. Multiple positions available. Requisition #: 4461661101

Your Skills and Experience

This position requires a Bachelor’s degree, or foreign equivalent, in Computer science, Computer Engineering, or a similarly quantitative and technical field and one (1) year of experience in the job offered or a related occupation.

Must have at least one (1) year of experience in each of the following skill(s):

• Applying analytical and engineering techniques to solve complex problems programmatically;
• Programming with Python;
• Developing and implementing algorithms and data structures;
• Software development lifecycle and best practices;
• Designing and developing software applications in a collaborative, cross-functional environment;
• Experience with DevOps, databases, big data, or frontend frameworks;
• Experience with Docker, Kubernetes, and Linux environments;
• Experience working with financial data;
• Foundational knowledge of quantitative trading concepts and equity/index options;
• Exposure to web/API frameworks such as FastAPI and React;
• Experience with automated testing and CI/CD pipelines;
• Experience collaborating with trading desks and developing software for use in a quantitative trading environment;
• Experience with the following tools: Team City, JIRA ticket management, Gerrit code review tool, GitLab, uv, Gitlab CI, py-spy, memray, and Python Packaging; and
• Experience with the following libraries: Pandas, Polars, NumPy, Tensorflow, Scikit, scikit-learn, cvxpy, and Pytest.

#LI-DNI

A DAY IN THE LIFE:

As an AI Software Engineer, you’ll spend your days architecting and building AI-powered systems that leverage foundational models like OpenAI, Claude, and Llama to solve real business problems. You’ll balance hands-on development of backend services and APIs with designing scalable AI integration patterns, building experimentation frameworks, and ensuring seamless deployment across our technology stack.

You’ll work closely with product managers to translate business needs into technical implementations, collaborate with data scientists on model integration, and guide teams on adopting the latest AI capabilities. You’ll drive rapid test-and-learn cycles, prototyping solutions that unlock significant business opportunities. You’ll also champion best practices for responsible AI implementation, ensuring our solutions are scalable, reliable, and maintainable.

This role is perfect for an expert generalist who thrives in fast-paced environments and wants to be at the forefront of AI innovation, turning cutting-edge technology into practical business solutions.

Team: Embedded within the AI Pathfinder team, collaborating across a cross-functional group of ~8–10 engineers, data scientists, and product managers within the Technology zone

Similar job titles: AI Platform Engineer, AI Engineer

WHAT WE’LL TRUST YOU TO DELIVER:

AI Solution Development

• Design and build backend services and APIs that deploy AI-powered features using foundational models
• Implement scalable architectures supporting AI workflows, automation, and data processing pipelines
• Create end-to-end solutions that translate high-level business problems into functional AI implementations
• Build experimentation frameworks enabling rapid iteration and deployment of AI functionalities

System Integration & Architecture

• Integrate AI services into complex technology stacks, ensuring seamless interoperability
• Connect AI capabilities with microservices, AWS platform components, and Redshift data systems
• Manage complex dependencies across multi-stack environments
• Ensure system reliability, scalability, and maintainability

Innovation & Experimentation

• Drive test-and-learn cycles with rapid prototyping of AI-driven solutions
• Evaluate and adopt new AI frameworks, tools, and capabilities
• Build proof-of-concept solutions for the company’s most exciting problems
• Stay current with the evolving AI ecosystem to guide technical decisions

Cross-Team Collaboration

• Partner with product managers to understand and translate business requirements
• Work with data scientists on model integration and optimization
• Coordinate with frontend engineers on API design and feature delivery
• Document system designs, APIs, and workflows for knowledge sharing

WHAT YOU LIKELY BRING TO THE TABLE: 

• 5+ years of backend software engineering with strong Python skills; experience with Java is a plus
• Proven track record designing and developing scalable APIs and distributed services (FastAPI, PostgreSQL, Redis)
• Deep understanding of cloud infrastructure (AWS Services, Bedrock), container orchestration (Kubernetes, Docker), and CI/CD pipelines
• Hands-on experience integrating AI/ML services and managing AI API dependencies (OpenAI, Claude, LangChain, vector databases)
• Practical knowledge of AI orchestration frameworks and data pipeline tooling (Redshift, Temporal)
• Test-and-learn mindset with strong rapid prototyping abilities
• Excellent communication skills for both technical and business stakeholders
• Experience with responsible AI principles, data privacy, and system reliability

Director, Software Engineering – Agentic Foundations (P4474)

PREFERRED LOCATION: Cincinnati / Chicago

SUMMARY:

The AI Enablement team at 84.51° is seeking a Director of Software Engineering for its Agentic Foundations team. This team is responsible for designing, developing, and maintaining the agentic backbone of the Kroger enterprise, including platforms, patterns, and tools to support the best practice development of AI agents.

The Director of Engineering requires a unique mix of software engineering and AI skills necessary to lead the technical design of platforms, patterns, and tools to support the enterprise agentic ecosystem. This role has a focus on providing the technical leadership needed for engineering and data science development teams implementing solutions like agent/MCP/scorer/prompt registries, agent-related tools to aid in the development and monitoring of best practice agents and tools, and managing low-code and no-code agent platforms that integrate with agentic support.

RESPONSIBILITIES:

• Partner with the Director of Product Management for Agentic Foundations to jointly lead the space for the Kroger enterprise
• Lead and manage a team of engineers, guiding them in the design and development of their product/platform areas and in the management of their own reports
• Lead and manage hiring efforts for engineers on the Agentic Foundations team, including finding interview panelists, writing interview guides and questions, and assisting with coding screening questions
• Own and manage offshore reliability engineering teams
• Provide in-depth technical leadership in the scoping and implementation of enterprise-grade solutions to support agents across the Kroger enterprise
• Provide operational leadership across agentic platforms, ensuring enterprise-grade reliability, observability, and incident management
• Maintain an up-to-date expertise on agentic workflows, frameworks, platforms, and best practices to identify and inform new capabilities for implementation
• Foster a collaborative and innovative team environment, encouraging professional growth and development among team members
• Reduce the development time of the team by leveraging agentic SDLC tooling provided by the enterprise
• Lead the abstraction of tooling and services to user-friendly interfaces like APIs, Python packages, or UIs
• Understand business requirements and trade-off scale, risk, and accuracy to maximize value and translate research into consumable products or services
• Guide the development teams to follow software development standards, including version control, documentation, testing, and support
• Make time-sensitive decisions and solve urgent problems without escalation

QUALIFICATIONS, SKILLS, AND EXPERIENCE:

• 7+ years professional experience with cloud-based software architecture focused on scalability, performance, and reliability
• 7+ years professional experience with end-to-end SDLC leveraging CI/CD and AIOps/MLOps, including experience with agentic SDLC tooling
• 7+ years professional experience with large-scale AI/ML systems, including 2+ years with GenAI and deep learning methods
• Professional experience with production-grade agentic systems, including concepts like design and development, evals, deployment, and monitoring
• Professional experience with AI/ML frameworks and tooling (PyTorch, OpenAI SDK, LangChain, autogen)
• Professional experience with AIOps/MLOps tooling and concepts (MLflow, Model Registry, Model Monitoring)
• Professional experience with scaling and deploying AI/ML systems using tooling in Microsoft Azure and Google Cloud, including CI/CD, containerization, orchestration, and API development (in particular FastAPI)
• Professional experience with Kubernetes (AKS) and Helm
• Professional experience with Python
• Professional experience with infrastructure-as-code using Terraform
• Professional experience leading technical teams and consulting with customers, including managing senior engineers, communicating complex technical topics, and driving outcomes in ambiguous environments
• Skilled in partnering with product management peers to jointly define product and team direction and priorities
• Education: Bachelor’s degree or higher in Software Engineering, Computer Science, Machine Learning, or a related field

#LI-SSS

#LI-Remote

Lead Software Engineer – Agentic Foundations (P4475, P4477)

LOCATION: Cincinnati / Chicago

SUMMARY:

The AI Enablement team at 84.51° is seeking a Lead Software Engineer for its Agentic Foundations team. This team is responsible for designing, developing, and maintaining the agentic backbone of the Kroger enterprise, including platforms, patterns, and tools to support the best practice development of AI agents.

The Lead Software Engineer will provide hands-on technical leadership across architecture, implementation, and operations of core agentic capabilities, including agent/MCP/scorer/prompt registries, evaluation and monitoring tooling, and low-code/no-code agent platforms that abstract complexity for developers and business users. You will partner closely with product management, data science, and engineering peers and leaders to deliver enterprise-grade capabilities that accelerate time-to-value, improve quality and reliability, and promote compliant, best-practice use of agentic systems.

RESPONSIBILITIES:

• Lead the design, development, and operation of core agentic platforms, services, and tooling used across the Kroger enterprise
• Own technical outcomes for a more specific product area, such as registries (agent/MCP/scorer/prompt), evaluation frameworks, observability/monitoring, SDKs/APIs/UIs, and low-code/no-code agent platforms
• Provide in-depth technical leadership to scope and implement scalable, secure, and reliable solutions;
• Uphold standards for architecture, code quality, testing, and documentation
• Partner with the Agentic Foundations leadership, as well as engineering and data science leads, to plan quarters/cycles/sprints and ensure efficient, predictable delivery
• Work with offshore reliability engineering teams to ensure SLAs are upheld
• Occasional participation in level 2 on-call support for production systems
• Abstract complex capabilities into developer-friendly interfaces (APIs, Python packages, CLIs, and UIs) to reduce friction and accelerate adoption
• Drive operational excellence across platforms, including incident management, on-call support, capacity planning, and cost optimization
• Mentor and guide engineers through code reviews, architecture discussions, and pairing; contribute to team growth, onboarding, and enablement

QUALIFICATIONS, SKILLS, AND EXPERIENCE:

• Professional experience with cloud-based software architecture focused on scalability, performance, and reliability
• Professional experience with end-to-end SDLC leveraging CI/CD and AIOps/MLOps, including experience with agentic SDLC tooling
• Professional experience with large-scale AI/ML systems, including 1+ years with GenAI and deep learning methods
• Professional experience with AI/ML frameworks and tooling (PyTorch, OpenAI SDK, LangChain, autogen)
• Professional experience with AIOps/MLOps tooling and concepts (MLflow, Model Registry, Model Monitoring)
• Professional experience with scaling and deploying AI/ML systems using tooling in Microsoft Azure and Google Cloud, including CI/CD, containerization, orchestration, and API development (in particular FastAPI)
• Professional experience with Kubernetes (AKS) and Helm
• Professional experience with Python
• Professional experience in ambiguous environments
• Skilled in problem solving, analytic thinking, and creativity
• Skilled in planning, organization, and verbal/written business communication
• Skilled in maintaining a positive leader persona in ambiguous and changing environments
• Demonstrated excellence as a teammate and leader
• 4-6 years relevant experience
• Education: Bachelor’s degree or higher in Software Engineering, Computer Science, Machine Learning, or a related field

#LI-SSS

#LI-Remote

Who we are:

At Focused, we move quickly to deliver quality software that achieves client outcomes and meets their customer’s needs. We strategically partner with our clients to leverage our expertise in design and software, while our clients bring their own domain expertise. We work with a variety of clients from different industries, collaborating as we get new products to market, modernizing legacy systems, or helping teams learn the skills they need to be successful.   

Our values:

• Listen first • We are experts in product practices but life long learners in the domain of our customers. We research, collaborate, and understand. 
• Learn why • We ask questions and talk to users to understand problem spaces, objectives, and goals, which allows us to deeply invest and drive towards the outcomes of our clients. 
• Love your craft • We love diving into a variety of domains and solving problems.  We take pride in delivering value, in communicating progress, and guiding our clients to success.

At Focused, our Engineers are both practitioners and experts in their craft. This role would play a crucial role in shaping and implementing engineering best practices and ensuring the successful delivery of complex software projects. With clients, we develop trust and influence - we are unintimidated and unintimidating. With colleagues, we set the standard for how we deliver success for clients.

What would you be doing?

• Build AI-enabled applications leveraging LangChain and LLMs to deliver meaningful, production-ready outcomes for clients.
• Deep expertise in LangChain, LangGraph and LangSmith.
• Lead teams through end-to-end delivery across the stack, from backend services to modern web UIs.
• Pair program daily with teammates and clients to share knowledge, improve code quality, and grow together.
• Practice TDD and continuous refactoring to ensure code is reliable, maintainable, and understandable.
• Guide architecture decisions to support scalability, observability, and performance.
• Collaborate closely with designers, product managers, and stakeholders to continuously deliver valuable software.
• Coach developers on the team through pairing, mentoring, and modeling healthy engineering culture.
• Influence technical direction beyond the team, working across client orgs and Focused’s internal practices to share lessons, shape approaches, and raise the collective bar.
• Stay curious through experimenting with new patterns in the GenAI space, share what works (and what doesn’t), and help evolve how we build AI-powered software.

We are excited about you, because you:

• You’re a hands-on, full stack engineer with a strong track record of delivering software in collaborative, agile environments.
• You’ve worked with LangChain (or similar agentic frameworks), and understand how to architect AI-native systems responsibly and effectively.
• You believe that code quality matters, and that TDD and pairing help build better systems and stronger teams.
• You’ve worked across multiple languages or frameworks (e.g., Python, Node, Java, React, Next.js) and are pragmatic about tool selection.
• You’re excited about what’s happening in the AI space but stay focused on delivering value.
• You have experience navigating complex organizations, building bridges across functions, and helping teams adopt modern development practices.
• You’re as comfortable in the code as you are in a client meeting and can translate technical risks and wins into language anyone can understand.
• You love to share what you’re learning and make the team around you better.

If you had worked at Focused over the last 3 months you may have:

• Paired with a teammate to build a document Q&A system using LangChain and OpenAI APIs
• Helped design an architecture that integrates LLM agents into a legacy enterprise workflow
• Refactored a flaky test suite to support continuous delivery with confidence
• Built and deployed a full stack GenAI MVP with a React frontend and FastAPI backend
• Facilitated an architecture spike to evaluate vector database options for semantic search
• Contributed a new section to our internal AI playbook
• Helped write this job req

What to know before you apply: 

• This role will require being in the Chicago office three days per week and up to 20% travel within the United States.
• Focused is unable to sponsor or take over sponsorship of the employment Visa process at this time.
• The Chicago base salary range for this role is $120,000 - $175,000.

Moonlite delivers high-performance AI infrastructure for organizations running intensive computational research, large-scale model training, and demanding data processing workloads.We provide infrastructure deployed in our facilities or co-located in yours, delivering flexible on-demand or reserved compute that feels like an extension of your existing data center. Our team of AI infrastructure specialists combines bare-metal performance with cloud-native operational simplicity, enabling research teams and enterprises to deploy demanding AI workloads with enterprise-grade reliability and compliance.

Your Role:

You will be foundational to building the comprehensive infrastructure platform that bridges our physical infrastructure –  bare-metal servers, GPU clusters, high-performance storage, and networking fabric – with the systems our customers depend on for large-scale computation, inference, simulations, and training. Working closely with product, your platform team members, and infrastructure specialists, you’ll design and implement the orchestration layer, APIs, and automation framework that make thousands of servers, petabytes of storage, and high-speed networks feel like a unified, programmable platform.    

Job Responsibilities

• Infrastructure Abstraction Layer: Design and build systems that bridge physical infrastructure (bare-metal servers, storage clusters, network fabric) with customer-facing services, enabling programmatic management of compute, networking, and storage at scale.
• Research Cluster Provisioning: Design and implement systems for provisioning and managing research computing environments including Kubernetes and SLURM clusters, enabling automated deployment, resource scheduling, and workload orchestration for distributed AI training and HPC workloads.
• Platform Orchestration: Implement comprehensive orchestration systems that coordinate across compute, storage and networking to deliver unified experience for complex research workloads.
• Network Automation & Placement: Design and build network provisioning automation including intelligent VM placement decisions for optimal network topology, automated VLAN and subnet configuration, and software-designed networking orchestration for high-performance interconnects.
• Enterprise APIs & SDKs: Develop robust APIs and SDKs that enable researchers and engineering teams to programmatically provision and manage infrastructure resources across all platform domains.
• Observability & Telemetry: Implement comprehensive observability, telemetry, and logging systems that provide visibility into infrastructure health, performance, and utilization across the infrastructure footprint.
• Performance Engineering: Build and optimize platform services that deliver consistent high-throughput low-latency networking for demand research applications and data-intensive workloads.
• Cross-Team Collaboration: Work closely with engineering, infrastructure, and product to define requirements, drive infrastructure-product-rollouts, and improve resource lifecycle management.
• Compliance & Security: Implement platform-wide compliance and security features supporting SOC 2, ISO 27001, and enterprise regulatory requirements including comprehensive audit logging, access controls, and data residency management.

Requirements

• Experience: 5+ years in software engineering with a proven track record of infrastructure platforms, distributed systems, or cloud platforms for production environments. 
• Kubernetes & Container Orchestration: Strong familiarity with Kubernetes architecture, container orchestration concepts, and experience deploying workloads in Kubernetes environments. Understanding of pods, deployments, services, and basic Kubernetes operations.
• Infrastructure Systems: Strong understanding of infrastructure fundamentals including compute orchestration, storage systems, networking technologies, and how they integrate together to deliver complete platform experiences.
• Programming Skills: Experience with systems programming languages (Go, C/C++, Rust, Python) for performance-critical components is a strong plus.
• Linux Production Experience: Strong experience with linux in production environments, including systems administration, performance tuning, and troubleshooting.
• Bare-Metal & Virtualization: Deep knowledge of bare-metal infrastructure, provisioning systems, out-of-band management, and virtualization technologies (KVM, Kubernetes, etc).
• API & Platform Design: Proven experience designing and building APIs, SDKs, and automation frameworks that enable programmatic infrastructure management.
• Cloud Platform Knowledge: Strong familiarity with cloud environments (AWS, GCP, Azure) and understanding of how to translate cloud-native patterns to bare-metal infrastructure.
• Infrastructure Automation: Experience with Infrastructure-as-code tools (Terraform, Ansible) and building automated deployment pipelines.
• Problem Solving & Autonomy: Self-starter who can navigate ambiguity, balance pragmatic shipping with good long-term architecture, and independently drive complex technical initiatives.
• Communication Skills: Strong written and verbal communication skills, including ability to write clear technical communication and collaborate across teams.
• Commitment to Growth: Growth mindset with continuous focus on learning and professional development.

Preferred Qualifications

• Background provisioning or managing research computing environments (Kubernetes, SLURM, or HPC clusters)
• Experience building internal platforms, infrastructure-as-a-service, or developer tooling
• Background with GPU computing platforms and AI/ML infrastructure requirements
• Knowledge of high-performance networking technologies (InfiniBand, RDMA, SR-IOV)
• Experience with observability and monitoring platforms (Prometheus, Grafana, ELK stack)
• Familiarity with both cloud-native and bare-metal infrastructure deployment models
• Understanding of enterprise compliance requirements and security best practices
• Extra points for experience with financial services technology infrastructure and understanding of trading system requirements

Key Technologies

• Go, Python, Kubernetes, Docker, Terraform, Ansible, Linux, Networking (BGP, VXLAN), Storage Systems, FastAPI, PostgreSQL, Redis, NVIDIA GPU Technologies, InfiniBand

Why Moonlite

• Build Next-Generation Infrastructure: Your work will create the platform foundation that enables financial institutions to harness AI capabilities previously impossible with traditional infrastructure.
• Hands-On Ownership: As an early engineer, you’ll have end-to-end ownership of projects and the autonomy to influence our product and technology direction.
• Shape Industry Standards: Contribute to defining how enterprise AI infrastructure should work for the most demanding regulated environments.
• Collaborate with Experts: Work alongside seasoned engineers and industry professionals passionate about high-performance computing, innovation, and problem-solving.
• Start-Up Agility with Industry Impact: Enjoy the dynamic, fast-paced environment of a startup while making an immediate impact in an evolving and critical technology space.

We offer a competitive total compensation package combining a competitive base salary, startup equity, and industry-leading benefits. The total compensation range for this role is $165,000 – $225,000, which includes both base salary and equity. Actual compensation will be determined based on experience, skills, and market alignment. We provide generous benefits, including a 6% 401(k) match, fully covered health insurance premiums, and other comprehensive offerings to support your well-being and success as we grow together.

#li-remote

Moonlite delivers high-performance AI infrastructure for organizations running intensive computational research, large-scale model training, and demanding data processing workloads. We provide infrastructure deployed in our facilities or co-located in yours, delivering flexible on-demand or reserved compute that feels like an extension of your existing data center. Our team of AI infrastructure specialists combines bare-metal performance with cloud-native operational simplicity, enabling research teams and enterprises to deploy demanding AI workloads with enterprise-grade reliability and compliance.

Your Role:

You will be foundational to building our software-defined networking (SDN) platform that enables high-performance, isolated networking for distributed computing, model training, inference, and data-intensive workloads. Working closely with our network, infrastructure, and product teams, you’ll design and implement the network orchestration and provisioning systems that manage DPU-accelerated networking, tenant isolation, and network lifecycle management – enabling researchers and engineers to access enterprise-grade networking with cloud-like simplicity.

Job Responsibilities:

• Software-Defined Networking Architecture: Collaborate with infrastructure to design and build scalable SDN orchestration systems leveraging NVIDIA Bluefield-3 DPUs to deliver programmable, high-performance networking for AI workloads with hardware-accelerated forwarding isolation.
• Research Cluster Networking: Design and implement networking systems for research computing environments including Kubernetes and SLURM clusters, enabling high-performance connectivity, optimized network topology for distributed workloads, and seamless integration with cluster orchestration systems.
• Network Provisioning & Lifecycle Management: Implement automated SDN provisioning systems that handle VPC creation, subnet allocation, routing configuration, and network resource lifecycle from deployment through decommissioning.
• DPU Platform Engineering: Develop platform capabilities for managing Bluefield-3 DPUs including SR-IOV virtual function management, OVS offload configuration, network function deployment, and integration with compute orchestration systems.
• Multi-Tenancy & Network Isolation: Build enterprise-grade network isolation using VPCs, VXLAN, and hardware-accelerated forwarding to ensure complete tenant separation while maintaining high-performance connectivity for GPU clusters and distributed workloads.
• High-Performance Networking: Collaborate with infrastructure to optimize network paths for RDMA, RoCE, and GPU-to-GPU communication, ensuring minimal latency and maximum throughput for distributed training and large-scale computational workloads.   
• Network APIs & Integration: Develop robust APIs and SDKs for network resource management that integrate seamlessly with compute and storage platforms, enabling programmatic network provisioning and configuration.
• Network Observability: Implement comprehensive network monitoring, telemetry, and troubleshooting systems that provide visibility into network performance, utilization, and tenant traffic patterns.Security & Policy Management: Build platform network security features including security groups, firewall rules, and policy enforcement that protect tenant workloads while enabling flexible network configuration.

Requirements:

• Experience: 5+ years in software engineering with proven experience building network platforms, SDN systems, or network automation for production environments.
• Kubernetes Networking & Container Orchestration: Strong familiarity with Kubernetes networking architecture, CNI plugins, service networking, and network policies. Understanding of pod networking, services, ingress, and how Kubernetes manages network resources.
• Networking Expertise: Deep understanding of networking fundamentals including TCP/IP, VLANs, VXLAN, BGP, OSPF, routing protocols, and data center network architectures.Software-Defined Networking: Background in SDN concepts, network virtualization, overlay networks, and programmable networking technologies.
• Programming Skills: Experience with Go and Python for performance-critical networking components and services is highly valued.
• Linux Networking: Strong experience with Linux networking stack, including network namespaces, iptables/nftables, Open vSwitch, and kernel networking systems.
• DPU & SmartNIC Experience: Familiarity with DPU/SmartNIC architectures (Bluefield, or similar), SR-IOV, hardware offload capabilities, and programmable networking hardware – or strong ability to learn quickly.
• High-Performance Networking: Understanding of RDMA, RoCE, Infiniband, and low-latency networking requirements for distributed computing and GPU workloads.
• Problem-Solving & Architecture: Demonstrated ability to solve complex networking performance and scalability challenges while balancing pragmatic shipping with good long-term architecture.
• Autonomy & Communication: Comfortable navigating ambiguity, defining requirements collaboratively, and communicating technical decisions through clear documentation.
• Commitment to Growth: Growth mindset with continuous focus on learning and professional development.

Preferred Qualifications

• Background provisioning or managing networking for research computing environments (Kubernetes, SLURM, or HPC clusters)
• Experience with NVIDIA Bluefield DPU programming and DOCA framework
• Background with network function virtualization (NFV) and service function chaining
• Knowledge of Kubernetes networking (CNI plugins, network policies, service mesh)
• Experience building network control planes or SDN controllers
• Familiarity with network automation frameworks and infrastructure-as-code for networking
• Understanding of data center fabric architectures (spine-leaf, CLOS topologies)
• Experience with network security and compliance requirements in regulated industries
• Background building networking for research institutions, HPC environments, or cloud providers

Key Technologies

• Go, Python, NVIDIA Bluefield DPUs, Open vSwitch, VXLAN, SR-IOV, RDMA, RoCE, InfiniBand, BGP, Linux networking, Terraform, FastAPI, gRPC

Why Moonlite

• Build Next-Generation Infrastructure: Your work will create the platform foundation that enables financial institutions to harness AI capabilities previously impossible with traditional infrastructure.
• Hands-On Ownership: As an early engineer, you’ll have end-to-end ownership of projects and the autonomy to influence our product and technology direction.
• Shape Industry Standards: Contribute to defining how enterprise AI infrastructure should work for the most demanding regulated environments.
• Collaborate with Experts: Work alongside seasoned engineers and industry professionals passionate about high-performance computing, innovation, and problem-solving.
• Start-Up Agility with Industry Impact: Enjoy the dynamic, fast-paced environment of a startup while making an immediate impact in an evolving and critical technology space.

We offer a competitive total compensation package combining a competitive base salary, startup equity, and industry-leading benefits. The total compensation range for this role is $165,000 – $225,000, which includes both base salary and equity. Actual compensation will be determined based on experience, skills, and market alignment. We provide generous benefits, including a 6% 401(k) match, fully covered health insurance premiums, and other comprehensive offerings to support your well-being and success as we grow together.

#li-remote

Moonlite delivers high-performance AI infrastructure for organizations running intensive computational research, large-scale model training, and demanding data processing workloads.We provide infrastructure deployed in our facilities or co-located in yours, delivering flexible on-demand or reserved compute that feels like an extension of your existing data center. Our team of AI infrastructure specialists combines bare-metal performance with cloud-native operational simplicity, enabling research teams and enterprises to deploy demanding AI workloads with enterprise-grade reliability and compliance.

Your Role:

You will be instrumental in building out our GPU-accelerated compute platform that powers distributed AI training and inference, large-scale simulations, and computational research workloads. Working closely with product, your platform team members, and infrastructure specialists, you’ll design and implement the compute orchestration layer that manages GPU clusters, bare-metal provisioning, and resource scheduling-enabling researchers and engineers to programmatically access high-performance compute resources with cloud-like simplicity.

Job Responsibilities

• Compute Orchestration Systems: Design and build scalable compute orchestration platforms that manage GPU clusters, bare-metal server provisioning, and resource allocation across co-located infrastructure environments.  
• Resource Management & Scheduling: Implement intelligent workload scheduling, resource allocation, and optimization algorithms that maximize GPU utilization while maintaining performance guarantees for research and training workloads.
• Research Cluster Provisioning: Design and implement systems for provisioning and managing research computing environments including Kubernetes and SLURM clusters, enabling automated deployment, resource scheduling, and workload orchestration for distributed AI training and HPC workloads.
• GPU Platform Engineering: Develop platform capabilities for managing latest-generation NVIDIA GPU configurations (H100, H200, B200, B300), including GPU resource management, multi-tenant isolation, and integration with compute orchestration systems.
• Bare-Metal Lifecycle Management: Build automation and tooling for complete bare-metal server lifecycle management – from initial provisioning and configuration through ongoing operations, updates, and resource reallocation.
• Performance-Critical Systems: Optimize compute platform components for high-throughput and low-latency performance, ensuring research workloads achieve near-bare-metal efficiency in virtualized or containersized environments.
• Platform APIs & Integration: Develop robust APIs and SDKs that enable researchers to programmatically provision and manage compute resources, integrating seamlessly with existing workflows and research infrastructure.
• Observability & Monitoring: Implement comprehensive monitoring and telemetry systems for compute resources, providing visibility into GPU virtualization, workload performance and infrastructure health.
• Multi-Tenancy and Isolation: Build enterprise-grade multi-tenant compute isolation, security boundaries, and resource quotas that enable safe sharing of GPU infrastructure across teams and organizations. 

Requirements

• Experience: 5+ years in software engineering with proven experience building compute platforms, container orchestration systems, or distributed compute infrastructure for production environments.
• Compute Platform Engineering: Strong background in building compute orchestration, resource scheduling, or workload management systems at scale.
• Kubernetes & Container Orchestration: Strong familiarity with Kubernetes architecture, container orchestration concepts, and experience deploying workloads in Kubernetes environments. Understanding of pods, deployments, services, and basic Kubernetes operations.
• Programming Skills: Experience with Go, C/C++, Python, or Rust for performance-critical components is highly valued. 
• Linux & Systems Programming: Strong experience with Linux in production environments, including systems for programming, performance optimization, and low-level resource management.
• Virtualization & Containers: Deep knowledge of virtualization technologies (KVM, Xen), container runtimes, and orchestration platforms. 
• GPU Computing Fundamentals: Understanding of GPU architectures, CUDA programming (where/when needed), and GPU resource management – or a strong ability to learn quickly.
• Bare-Metal Infrastructure: Experience with bare-metal provisioning, out-of-band management systems, and hardware abstraction layers.
• Problem-Solving & Architecture: Demonstrated ability to solve complex performance and scalability challenges while balancing pragmatic shipping with good long-term architecture. 
• Autonomy & Communication: Comfortable navigating ambiguity, defining requirements collaboratively, and communicating technical discussions through clear documentation.
• Commitment to Growth: Growth mindset with continuous focus on learning and professional development.

Preferred Qualifications

• Background provisioning or managing research computing environments (Kubernetes, SLURM, or HPC clusters)
• Experience with GPU virtualization technologies (SR-IOV, NVIDIA vGPU) and multi-tenant GPU sharing
• Background in container orchestration platforms with custom scheduling or resource management
• Knowledge of high-performance networking for GPU communication (InfiniBand, RDMA, NVLink, NVSwitch)
• Familiarity with AI/ML training frameworks (PyTorch, TensorFlow) and their infrastructure requirements
• Understanding of distributed training patterns and multi-node GPU coordination
• Experience building infrastructure for research institutions,labs, or technical computing environments
• Background in financial services or other regulated industry infrastructure is a plus

Key Technologies

• Go, C/C++, Python, KVM, Docker, Kubernetes,, NVIDIA GPUDirect, SR-IOV, NVIDIA vGPU, CUDA, InfiniBand, RDMA, Terraform, FastAPI, gRPC, Linux systems programming

Why Moonlite

• Build Next-Generation Infrastructure: Your work will create the platform foundation that enables financial institutions to harness AI capabilities previously impossible with traditional infrastructure.
• Hands-On Ownership: As an early engineer, you’ll have end-to-end ownership of projects and the autonomy to influence our product and technology direction.
• Shape Industry Standards: Contribute to defining how enterprise AI infrastructure should work for the most demanding regulated environments.
• Collaborate with Experts: Work alongside seasoned engineers and industry professionals passionate about high-performance computing, innovation, and problem-solving.
• Start-Up Agility with Industry Impact: Enjoy the dynamic, fast-paced environment of a startup while making an immediate impact in an evolving and critical technology space.

We offer a competitive total compensation package combining a competitive base salary, startup equity, and industry-leading benefits. The total compensation range for this role is $165,000 – $225,000, which includes both base salary and equity. Actual compensation will be determined based on experience, skills, and market alignment. We provide generous benefits, including a 6% 401(k) match, fully covered health insurance premiums, and other comprehensive offerings to support your well-being and success as we grow together.

#li-remote

Who we are:

At Focused, we move quickly to deliver quality software that achieves client outcomes and meets their customer’s needs. We strategically partner with our clients to leverage our expertise in design and software, while our clients bring their own domain expertise. We work with a variety of clients from different industries, collaborating as we get new products to market, modernizing legacy systems, or helping teams learn the skills they need to be successful.   

Our values:

• Listen first • We are experts in product practices but life long learners in the domain of our customers. We research, collaborate, and understand. 
• Learn why • We ask questions and talk to users to understand problem spaces, objectives, and goals, which allows us to deeply invest and drive towards the outcomes of our clients. 
• Love your craft • We love diving into a variety of domains and solving problems.  We take pride in delivering value, in communicating progress, and guiding our clients to success.

At Focused, our Engineers are both practitioners and experts in their craft. This role would play a crucial role in shaping and implementing engineering best practices and ensuring the successful delivery of complex software projects. With clients, we develop trust and influence - we are unintimidated and unintimidating. With colleagues, we set the standard for how we deliver success for clients.

What would you be doing?

• Build AI-enabled applications leveraging LangChain and LLMs to deliver meaningful, production-ready outcomes for clients.
• Deep expertise in LangChain, LangGraph and LangSmith
• Lead teams through end-to-end delivery across the stack, from backend services to modern web UIs.
• Pair program daily with teammates and clients to share knowledge, improve code quality, and grow together.
• Practice TDD and continuous refactoring to ensure code is reliable, maintainable, and understandable.
• Guide architecture decisions to support scalability, observability, and performance.
• Collaborate closely with designers, product managers, and stakeholders to continuously deliver valuable software.
• Coach developers on the team through pairing, mentoring, and modeling healthy engineering culture.
• Influence technical direction beyond the team, working across client orgs and Focused’s internal practices to share lessons, shape approaches, and raise the collective bar.
• Stay curious through experimenting with new patterns in the GenAI space, share what works (and what doesn’t), and help evolve how we build AI-powered software.

We are excited about you, because you:

• You’re a hands-on, full stack engineer with a strong track record of delivering software in collaborative, agile environments.
• You’ve worked with LangChain (or similar agentic frameworks), and understand how to architect AI-native systems responsibly and effectively.
• You have experience leading engineering teams and feel confident mentoring and supporting other developers.
• You believe that code quality matters, and that TDD and pairing help build better systems and stronger teams.
• You’ve worked across multiple languages or frameworks (e.g., Python, Node, Java, React, Next.js) and are pragmatic about tool selection.
• You’re excited about what’s happening in the AI space but stay focused on delivering value.
• You have experience navigating complex organizations, building bridges across functions, and helping teams adopt modern development practices.
• You’re as comfortable in the code as you are in a client meeting and can translate technical risks and wins into language anyone can understand.
• You love to share what you’re learning and make the team around you better.

If you had worked at Focused over the last 3 months you may have:

• Paired with a teammate to build a document Q&A system using LangChain and OpenAI APIs
• Helped design an architecture that integrates LLM agents into a legacy enterprise workflow
• Refactored a flaky test suite to support continuous delivery with confidence
• Mentored a junior dev through their first pairing and TDD session
• Built and deployed a full stack GenAI MVP with a React frontend and FastAPI backend
• Facilitated an architecture spike to evaluate vector database options for semantic search
• Contributed a new section to our internal AI playbook
• Helped write this job req

What to know before you apply: 

• This role will require being in the Chicago office three days per week and up to 20% travel within the United States.
• Focused is unable to sponsor or take over sponsorship of the employment Visa process at this time.
• The Chicago base salary range for this role is $175,000 - $250,000.