As an MLOps Team Leader, you will own our AI infrastructure and backend engineering efforts, leading a team at the intersection of systems design and machine learning to build the engineering systems that turn Deep Learning and Computer Vision research into reliable, scalable production features.

What Youll Be Doing:
Lead MLOps Engineering: Own the roadmap and execution for a team of backend and AI infrastructure/MLOps engineers, setting technical direction, removing blockers, and holding the bar on delivery quality.
Build Production AI Systems: Design and implement production-grade, end-to-end AI solutions, including agentic workflows, that integrate Deep Learning models and Computer Vision algorithms into real features. Own the offline experimentation and validation layer, including POC environments that let the Algo team move from research to production confidently.
Architect Data Platforms: Drive the design and implementation of scalable data platforms and pipelines that power our AI capabilities reliably and with an eye on cost and scale.
Cross-functional Collaboration: Work closely with the Algorithms and Data teams to tackle complex, real-world problems, translating research into shippable, maintainable systems.
Elevate Engineering Standards: Champion Software Engineering and System Design best practices across the group, introducing the right methodologies, tooling, and culture of craft.

As a Backend Team Leader, you will lead a team of backend and MLOps engineers that owns the systems behind our AI-driven product features. Your team works closest to our AI group - the Algorithms and Data teams - and owns the engineering side of turning models into reliable production capabilities.

Concretely, that means owning real backend architecture - the services and APIs that carry AI-driven capabilities into the product, the data collection pipelines that feed model training, the storage and query layers that hold model outputs and the insights we derive from them, and the validation pipelines that let us trust production flows. You will make the core design decisions on service boundaries, data models, event flows, and scale and cost tradeoffs, in a domain where both the data volume and the correctness bar are high. You do not need to arrive as an ML expert. You do need to be the kind of engineer who walks into an unfamiliar domain, learns it properly, and starts making good decisions in it.

What you'll be doing -

Lead and grow the team
Manage backend and MLOps engineers, some embedded in product pods; coach on delivery, decision-making, and career growth
Set clear expectations for ownership and quality; track progress against team goals, surfacing risks early.

Own the backend behind our AI features
Build and scale data pipelines with the AI group, and design how model insights are stored, queried, and exposed to the product
Build validation pipelines and partner with the Algo team to take models from experiment to production.

Drive architecture direction and alignment
Align backend decisions with the wider group, guide design discussions, and keep specs and plans on time
Collaborate with the platform team on infrastructure, deployment, and reliability standards.

Improve reliability and operational readiness
Raise the bar on stability, observability, and alert quality
Turn recurring issues into focused engineering work; lead debriefs and drive action items to completion.

We're looking for a hands-on Senior backend Engineer to join the App Studio & Intelligence team within Earnix's GenAI Group. Our group builds the company's core Generative AI products - including a company-wide agents platform and customer-facing AI assistants - enabling teams across Earnix and our customers to design and deploy AI-driven solutions. In this role, you'll design and build scalable microservices and cloud-native infrastructure at the heart of our GenAI applications, working with advanced AI capabilities such as knowledge bases, embeddings, LLM orchestration, agent frameworks, and evaluation systems. You'll be a senior technical voice on the team - owning complex features end-to-end, raising the engineering bar, and shaping how AI capabilities are delivered in production.
?What You'll Do Design, build, and own backend services and infrastructure for our GenAI applications - scalable, resilient, production-grade systems running on AWS. Build the APIs, data pipelines, and backend integrations that power advanced AI capabilities, including knowledge bases, embeddings, LLM orchestration, agent workflows, and evaluation frameworks, with attention to performance, scalability, and security. Lead complex design efforts - driving architecture discussions, design reviews, and technical decisions for significant areas of the system. Collaborate closely with product, data science, and other engineering teams to translate business needs into robust backend solutions that enable AI-agent use cases. Raise the engineering bar through code reviews, mentoring less experienced engineers, and championing best practices in quality, observability, and operational excellence. Take ownership of production health, including monitoring, alerting, troubleshooting, and continuously improving system reliability.

Position Intro:
Earnix is the first AI company purpose-built for insurance decisioning, providing the industry with the intelligence, governance, and decisioning agility to drive profitable growth, improve resilience, and operate with speed and precision in a rapidly changing risk environment. A trusted provider of production-grade AI and decisioning technology, Earnix builds on more than 25 years of experience in artificial intelligence risk, pricing, rating, analytics, and decisioning. Earnix brings vertical AI into the workflows and decisions that shape insurance performance across insurers pricing, underwriting, claims, customer engagement, retention, and other insurers high-value insurance moments. Earnixs AIOS enables insurers to orchestrate intelligence across the insurance decision lifecycle and drive governed, Real-Time decisions that deliver measurable business outcomes. Earnix is headquartered in Boston, MA and has been innovating for insurers and banks since 2001 with customers in over 35 countries across six continents and offices in the Americas, Europe, Asia Pacific, and Israel.

we are the AI-native platform powering the era of Agentic HR. Powered by Loomra, our context engine is purpose-built for the workforce. our company lets you build any Agentic HR agent that operates in the flow of work across Slack, Microsoft Teams, Copilot, and Google Chat. Talent Redeployment, internal mobility, skills intelligence, workforce redesign, and whatever comes next.
Trusted by leading global enterprises, our company serves over 1.5 million employees across 30+ Fortune 500 companies, unlocking more than 4.8 million strategic work hours. We help organizations harness AI to unlock agility, productivity, and growth, empowering them to achieve true ROI and drive exponential productivity.
About the Role
We are seeking an experienced and passionate Senior Software Engineer to join our core engineering team. In this role, you will design, build, and scale high-performance backend services that power our enterprise Agentic AI platform. You will tackle complex technical challenges, architect robust systems, and work on cutting-edge features that seamlessly integrate AI agents into enterprise workflows.
As a Senior Software Engineer at our company, you will collaborate closely with product managers, and cross-functional engineering teams. You will take full ownership of end-to-end feature delivery from initial system design and API definition to production monitoring and optimization - ensuring our platform maintains top-tier reliability, security, and execution velocity.
Responsibilities
Design, architect, and maintain highly scalable, high-throughput backend services and distributed systems.
Take end-to-end ownership of features and projects, driving them from technical design through to deployment and monitoring.
Build and optimize core APIs and integration layers.
Write clean, testable, and maintainable code, adhering to software engineering best practices (CI/CD, code reviews, automated testing).
Drive architectural decisions, lead technical design discussions, and advocate for system performance and scalability improvements.
Troubleshoot and resolve complex production issues, ensuring high system availability and low latency.
Mentor and guide junior and mid-level software engineers, driving engineering excellence across the team.

We're looking for a hands-on Senior Backend Engineer to join the App Studio & Intelligence team within GenAI Group. Our group builds the company's core Generative AI products - including a company-wide agents platform and customer-facing AI assistants - enabling teams across and our customers to design and deploy AI-driven solutions.
In this role, you'll design and build scalable microservices and cloud-native infrastructure at the heart of our GenAI applications, working with advanced AI capabilities such as knowledge bases, embeddings, LLM orchestration, agent frameworks, and evaluation systems. You'll be a senior technical voice on the team - owning complex features end-to-end, raising the engineering bar, and shaping how AI capabilities are delivered in production.
What You'll Do:
Design, build, and own backend services and infrastructure for our GenAI applications - scalable, resilient, production-grade systems running on AWS.
Build the APIs, data pipelines, and backend integrations that power advanced AI capabilities, including knowledge bases, embeddings, LLM orchestration, agent workflows, and evaluation frameworks, with attention to performance, scalability, and security.
Lead complex design efforts - driving architecture discussions, design reviews, and technical decisions for significant areas of the system.
Collaborate closely with product, data science, and other engineering teams to translate business needs into robust backend solutions that enable AI-agent use cases.
Raise the engineering bar through code reviews, mentoring less experienced engineers, and championing best practices in quality, observability, and operational excellence.
Take ownership of production health, including monitoring, alerting, troubleshooting, and continuously improving system reliability.

We are looking for a Software Engineer to help design and develop the core services and applications that drive our data capabilities. In this role, you will build high-quality, scalable software; contribute to the architecture of our next-generation data systems; and collaborate with research and product teams to turn cutting-edge ideas into production-ready features.
Responsibilities:
Design, develop, and maintain scalable backend services and components that power our data workflows, analytics, and product features.
Build high-quality internal tools and applications that improve engineering workflows and enable data-driven development across the organization.
Contribute to the architecture and evolution of our new data platform with a strong focus on clean design, testability, maintainability, and performance.
Collaborate closely with security researchers, analysts, and product managers to translate innovative cybersecurity concepts into reliable, production-ready software.
Apply engineering best practices across the stack - including code quality, testing, observability, versioning, and documentation - to ensure system robustness as we scale.

We are looking for a skilled and motivated Senior Python Backend Engineer to join our Surveillance Engineering team. The ideal candidate will have a deep understanding of software development and technical expertise. This is a hands-on role for someone who wants both depth and ownership: youll design and build complex components, drive architecture and technology-selection decisions, and stay close to the product in production. The position requires strong collaboration and communication skills as you will be working alongside engineers, data scientists, and domain experts.

About the Surveillance Group: The Surveillance group at our company builds and operates advanced AI solutions. Our team is composed of engineers, data scientists and subject matter experts who work together to deliver a high-quality, production-ready Surveillance product. We push the boundaries of what is possible and measure ourselves by the impact we deliver to our clients.

Lets get down to business:

What Youll Do:

Design, build and maintain the software infrastructure and solutions that make up our Surveillance pipeline, combining classic machine learning models and GenAI models with complex business logic and analytical components.
Own significant architecture decisions and evaluate and select the technologies we build on.
Solve complex engineering problems end to end, from investigation and design through implementation and rollout.
Collaborate with engineers, data scientists and subject matter experts to deliver high-quality, production-ready that are fully integrated and scalable.
Support the product in production: investigate issues, improve observability, and make the system easier to run.
Build and operate services in containerized environments (Docker, Kubernetes) on AWS.
Hold a high engineering bar: meaningful unit tests, solid CI/CD following best practices.
Keep current with developments in software engineering and production ML infrastructure.

Were looking for a Senior Backend Engineer to join mobility engineering group and build the systems behind one of the worlds largest location-analytics platforms.
In this role, youll work on backend services that process and serve millions of clients, power ML-driven insights, and operate at high scale and high reliability. If youre motivated by hard technical challenges, modern infrastructure, and collaborating with strong engineers, this role is built for you.
RESPONSIBILITIES:
Own services end-to-end - from architecture and design to production, monitoring, and continuous improvement
Drive performance, scalability, and reliability, using data and metrics to guide decisions
Build infrastructure and data pipelines that support machine-learning, analytics, and real-time use cases
Partner closely with Product, Data Science, and Analytics to turn complex data into impactful product features
Raise the engineering bar through code reviews, design discussions, and technical mentorship

We are looking for a highly driven and experienced AI Engineer Team Leader to manage and mentor a core team of engineers while remaining 50% hands-on. In this critical role, you will lead the development of our enterprise Agentic AI platform, blending deep technical expertise in AI agent development with strong engineering leadership.
As a Team Leader, you will drive the technical agenda, plan sprints, and collaborate closely with Product Managers and cross-functional partners to turn powerful capabilities into reliable, safe, and fast product experiences. You must thrive in a high-pressure, dynamic startup environment characterized by a fast pace and frequent pivots, ensuring your team remains focused, agile, and aligned with business goals while executing at the highest level.
You won't just manage - you'll own agent workflows end to end, from design through evaluation, deployment into the tools employees use daily, and iteration in front of enterprise customers.
Responsibilities
Team Leadership & Management (50%): Manage, mentor, and grow a team of AI and software engineers. Oversee task allocation, sprint planning, and daily agile ceremonies.
Hands-On Engineering (50%): Actively code, design, and build multi-agent systems and orchestration - intent routing, planning, tool use, and coordination across specialized agents.
Technical Strategy & Architecture: Drive the technical agenda, architecture decisions, and best practices for developing scalable, LLM-driven applications grounded in our knowledge graph.
System Integration: Integrate LLMs with tool/function calling and protocols such as MCP to give agents controlled access to HCM systems, business logic, and workflows.
Production Excellence: Build evaluation harnesses, guardrails, and safety/bias checks. Optimize agents for latency, cost, and reliability at enterprise scale. Take agents from prototype to production - with monitoring, observability, and a fast iteration loop.
Cross-Functional Collaboration: Work intimately with Product Management, Data, and Design teams to translate customer needs into agent capabilities, define roadmaps, and prioritize tasks.
Agility & Execution: Lead the team through frequent pivots and rapid development cycles, ensuring high-quality delivery under pressure in a fast-paced startup environment.

We are hiring an Engineering Manager to own and grow the Data Science group - the R&D team behind our company's security and safety AI models and the data platform that powers them. You will lead a multidisciplinary team of ML engineers, data scientists, and software engineers who ship real-time inference at scale, automated red-teaming of GenAI systems, and the Databricks/Spark data platform underneath. This is a hands-on people-leadership role: you set technical direction, are accountable for delivery and quality, and you build and grow the team.
What your team owns
The group is responsible for a large Python + Rust + PySpark monorepo (dozens of production services and shared libraries) spanning three connected domains:
1. Content-moderation inference at scale
Real-time, multi-tenant detection across text, image, video, and audio - hate speech, CSAM, nudity, child grooming, extremism, PII, prompt injection, age estimation, and more - served through an in-house ActiveServe framework over NVIDIA Triton and a Rust detection monolith, on latency-sensitive, SLA-bound, customer-facing traffic with per-customer custom models.
2. GenAI safety & red-teaming
Automated red-teaming that attacks customers' LLM applications with a research-driven attack taxonomy and measures attack-success rate, alongside the defensive side - LLM-as-judge escalation to cut false positives and the tooling that authors and refines moderation policies - built on a multi-provider LLM foundation (Bedrock, Anthropic, OpenAI, Gemini, xAI Grok) and forming our company's leading edge into agentic-AI safety.
3. Data platform & MLOps
An end-to-end lakehouse and MLOps stack on Databricks - bronze/silver/gold ingestion, PySpark pipelines, and model training, versioning, and promotion through MLflow / Unity Catalog into Triton serving - with the performance-critical hot paths engineered in Rust (PyO3/maturin) for sub-millisecond, high-QPS matching and detection.
What you'll do
Lead and grow the team - mentor ML engineers, data scientists, and software engineers, and own hiring, onboarding, 1:1s, career development, and performance.
Set direction and deliver - set technical direction and standards, turn company and product goals into a prioritized roadmap, and own the quality, reliability, and delivery of the systems above across parallel workstreams.
Champion excellence and partnership - stay hands-on to review designs and unblock the team, drive engineering excellence (testing, observability, CI/CD, on-call, cost/latency), keep the team at the state of the art in ML, LLMs, and GenAI safety, and partner with Product, Platform, and GenAI-safety stakeholders.
Leadership competencies
People-first: builds trust, grows engineers, and creates a healthy, inclusive, high-ownership culture.
Outcome-oriented: drives clarity, sets priorities, and delivers under ambiguity without micromanaging.
Technical credibility: earns the team's respect through sound judgment on architecture and trade-offs.
Systems thinker: balances short-term delivery against long-term platform health, cost, and tech debt.