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We're looking for a strong Senior Backend Engineer, the team building our AI security products. This is one of the most exciting places to be at right now: a brand-new product, in a domain that changes every day, with real customers already shaping what we build next.
You'll join a small, senior, globally distributed team of six engineers across Europe, Israel and Argentina. You'll own features end to end, from the first conversation with Product through design, build, and production. Because the domain is new, your technical judgment will shape the architecture rather than follow it.
If you want to build something genuinely new, at the point where AI and security meet, let's talk.
What You'll Be Doing:
Design and build the backend of our AI security products in Node.js and TypeScript, running across cloud environments and endpoints
Own features end to end, from business requirements through architecture, implementation, delivery and production quality
Work closely with Product and directly with customers, turning fast-moving business needs into robust technical solutions
Partner with Product, Design, and other engineering teams on complex cross-company projects
Make and defend architectural decisions in a domain with no established playbook, where the right answer this quarter may not be the right answer next quarter
Set the technical bar for a senior team, and raise it through code reviews, design discussions and examples

We are looking for a Deep Learning Engineer to help design, implement, optimize, and scale the training and inference systems behind our models.

What you'll do
Collaborate with cross-functional teams to bring research breakthroughs into production environments.

Build tools, abstractions, and infrastructure that make model training, evaluation, and deployment faster and more reliable.

Analyze and overcome performance and scalability challenges in large-scale distributed training.

Debug complex issues across the full ML stack: data loading, model code, distributed execution, GPU utilization, memory usage, networking, checkpointing, and serving.

Work with modern training and inference frameworks such as Megatron, TorchTitan, PyTorch, and vLLM.

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 are looking for a Product Engineer to own and ship the products that put this capability in the hands of engineers, data scientists, and researchers.

What you'll do
Own product features end-to-end: scope, build, ship, measure, and iterate - across CLI, IDE integrations, web surfaces, and the AI pipeline behind them.

Talk directly to users - engineers, data scientists, ML practitioners - and let their feedback shape what you build next.

Define what AI-powered code optimization and verification feels like as a developer experience: the interaction model, the feedback loops, the trust signals. There is no established playbook; you will create the conventions.

Craft interfaces that feel fast, focused, and effortless for technical users who have zero patience for friction.

Collaborate with researchers to translate model breakthroughs into polished, reliable tooling that developers can depend on in production.

Build evaluation infrastructure and product metrics that measure whether the tools are actually getting better.

Work directly with the founding team on product strategy and roadmap.

Our group is responsible for building software enabling both the large-scale quantitative research operations that drive our platform and the production of our portfolio. The team is currently embarking on a multi-year journey to provide a powerful, scalable, and efficient platform to drive the firms next decade of growth. We are looking for someone who can own some of the unique technical challenges inherent in the problem and who can bring solid experience and perspective to the team.

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.

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.

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 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.