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We are looking for an experienced Software Engineer (4+ years) to join the team as an AI Integration Engineer, supporting one of our enterprise clients as part of their AI-Native Development program.
In this role, you will act as an AI Champion and Technical Mentor within the clients R&D organization. Your mission is to help development teams effectively integrate AI tools, agentic coding workflows, and best practices into their daily software development lifecycle (SDLC). You will help guide teams through AI adoption, help overcome resistance, and ensure AI delivers real value.
This is not a feature-delivery or coding-focused role, especially in the early stages, the position is centered on enablement, training, and integration, working closely with teams to embed AI development tools into real workflows and support the organizations AI transformation.
This is a high-impact role focused on technical enablement, AI expertise, and effective collaboration with development teams, and intended for experienced engineers who actively use AI in their day-to-day development work and are looking to influence how teams work, rather than for junior profiles or engineers seeking a purely coding-focused position
What Youll Do:
Help drive adoption and optimization of Claude Code and/or similar Agentic coding tools
Support software and QA engineers, answer technical questions and help unblock teams
Stay on the cutting edge of AI releases and best practices, turn your learnings into shareable assets (custom rules, agents, skills, demos, playbooks, etc.)
Measure impact, identify gaps and improvement opportunities across the SDLC
Help defuse resistance to change with patience and empathy
Partner with DevOps, architects and management to track and optimize AI utilization.

We're forming a new AI Group and looking for a Senior AI Engineer to help shape it from an early stage - a greenfield, long-term effort to evolve how decisions are made across the platform using AI-driven systems. You won't just integrate APIs or build demos; you'll build the AI brain that works alongside (and increasingly drives) our core automation engine, with real production impact from day one and room to grow into technical leadership as the group scales.

Agentic AI Architecture: Design and build autonomous AI agents that analyze infrastructure in real time and make intelligent decisions. Work with modern agentic frameworks (LangGraph, PydanticAI) and conversational AI to create multi-agent systems - including troubleshooting, optimization, FinOps, and how-to agents. Leverage core LLM capabilities (tool-use, memory, retrieval) to operate safely in production.
Platform Integration & Intelligent Decision Systems: Develop MCPs to expose capabilities to AI agents that reason over infrastructure environments, metrics, configurations, and cost signals. Build integrations with tools like Slack, Jira, and AI-powered IDEs (Cursor, Windsurf) to deliver context-aware insights, from "why is this pod not scheduling?" to "how can we reduce costs by 30% safely?"
AI Model Development & MLOps: Build and deploy machine learning models that learn from infrastructure patterns - detecting the right resource policies for workloads, predicting optimal scaling triggers, and recommending GPU configurations. Own the complete ML pipeline from training to production, ensuring models are reliable, monitored, and continuously improving.
R&D AI Tools Development & Adoption: Build and embed internal AI tools to accelerate engineering, development, research, and support.
AI Tools for Business Impact: Develop AI-powered tools that help Sales and Support teams demonstrate value instantly - agents that analyze customer infrastructure, generate cost optimization reports automatically, and turn technical data into clear business recommendations.
End-to-End Ownership: Own AI systems from concept to production, ensuring they're fast (sub-2-second responses), reliable, safe, and cost-effective. Build evaluation frameworks to measure quality, implement security controls, and balance performance tradeoffs in production.
Technical Leadership: Define AI architecture and best practices as a founding member of the AI team. Make key technical decisions - choosing frameworks, designing multi-agent systems, establishing data governance - and shape how evolves from AI-enhanced internal tools to customer-facing AI products.

As a DevOps Engineer , you'll be a technical authority in everything cloud-native - leading feature development, making key architectural decisions, and collaborating with cross-functional teams to drive innovation.

Take an active role across all DevOps areas: infrastructure and cloud environment, tools, services, and uptime.
Contribute to the product's architectural and infrastructure design; evaluate and implement new cloud technologies and open-source tools to improve delivery and availability of the product.
Plan and drive the growth and scale of data capacity across products.
Own the smooth, production-grade execution of delivered solutions.

We're seeking a talented, experienced Frontend Engineer to join our Engineering team, tackling complex engineering challenges daily, improving our solutions, and driving innovation in Kubernetes optimization while working with cutting-edge technologies alongside major cloud providers such as AWS, GCP, and Azure.

Join a team of top-notch, skilled professionals building our core product offering
Build a world-class Kubernetes resource management platform that improves the productivity of DevOps teams across the world
Own the design and implementation of top-tier UI components, ensuring a smooth user experience
Enjoy a high degree of autonomy and responsibility
Make a high impact on the company's future, working on the core product while collaborating with top-tier engineers in a culture of innovation

We are building the autonomous infrastructure management platform that will power the next decade of enterprise compute.

What You Will Be Doing
Lead and grow a high-performing engineering organization responsible for our core product offering.
Define and execute the engineering strategy for our Kubernetes resource management platform, enabling DevOps teams worldwide to operate more efficiently.
Partner closely with Product, Design, and Go-to-Market leaders to translate business strategy into engineering execution.
Drive technical excellence, architectural direction, and engineering best practices across multiple teams.
Build, mentor, and develop engineering managers and senior engineers, fostering a culture of ownership, innovation, and continuous improvement.
Scale engineering processes, organizational structure, and delivery capabilities while maintaining a high bar for quality and execution.
Balance hands-on technical leadership with organizational leadership, making key architectural and strategic decisions when needed.
Create an environment where talented engineers can do their best work with a high degree of autonomy, accountability, and collaboration.

As a Senior DevOps Engineer on the Price-It Platform team, youll own core cloud infrastructure, CI/CD, and the Kubernetes platform that powers Earnixs cloud-based decisioning products for global insurers and banks. Youll take end-to-end technical ownership of high-impact platform initiatives - from design through production - working hands-on across AWS, Kubernetes, and automation, while shaping how the team builds and ships.
What You'll Do: Own and evolve the cloud platform: AWS infrastructure, EKS/Kubernetes, and Terraform-based Infrastructure-as-Code. Build and maintain CI/CD pipelines and GitOps workflows that keep delivery fast, safe, and repeatable. Design and operate secure networking and access (ALB, OIDC/OAuth2, JWT/M2M, Okta, firewalling). Drive reliability, scalability, and resilience - including disaster recovery and multi-region readiness. Partner closely with R&D, Product, QA, and Support to take initiatives from design to production. Improve Developer experience and velocity, including through AI-assisted and agentic engineering workflows. Mentor and raise the engineering bar through technical leadership, design reviews, and documentation.
Position Intro:
Earnix is the premier provider of mission-critical, cloud-based intelligent decisioning across pricing, rating, underwriting, and product personalization. These fully-integrated solutions provide ultra-fast ROI and are designed to transform how global insurers and banks are run by unlocking value across all facets of the business. Earnix 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.

The role is simple to state and hard to do well: make that optimization save more tokens without ever costing output quality or breaking a provider's cache. It's a research-heavy engineering role - you form theories from real traffic and ship the ones that prove out on live customer requests.

Why this role
LLM optimization is a young field with no settled playbook, so the optimizations you invent here are genuinely new - and they ship into production, not a paper. And they matter: real enterprises run enormous volumes of LLM traffic and feel every wasted token, so the work you do lands on live customer requests and solves a problem they actually have. It's about as close to the frontier, and as close to the product, as engineering gets.

LLM optimization is a young field with no settled playbook, so the optimizations you invent here are genuinely new - and they ship into production, not a paper. And they matter: real enterprises run enormous volumes of LLM traffic and feel every wasted token, so the work you do lands on live customer requests and solves a problem they actually have. It's about as close to the frontier, and as close to the product, as engineering gets.

03What you'll do
Invent and ship optimizations. Design new strategies across every layer of a request - prompt and context compression, tool pruning, file and dev-command trimming, semantic caching, cache-prefix stabilization - and take them all the way to the hot path. Each one has to cut tokens on real traffic without degrading output.
Prove every win. Build the evals and the token/quality instrumentation that separate a genuine saving from a plausible-sounding one. An optimization only ships when the numbers back it.
Live in the caching trade-offs. Provider prompt caches only pay off on byte-stable prefixes, and a naive rewrite can cost more than it saves. Knowing exactly when an optimization actually wins - deterministic transforms, per-session decision pins, semantic dedup - is a lot of the job.
Build and own the gateway that runs them. The real-time proxy that carries production LLM traffic - streaming, retries, backpressure - executing every optimization on the live request path.
Keep it fast and deploy anywhere. Defend a tight latency budget on the hot path, and package the whole thing so it installs cleanly into any customer's cloud - AWS, GCP, Azure, containers, Kubernetes - and upgrades without drama.
Own systems end to end. From first commit to code serving live customer traffic - plus the spend-visibility and governance product built on top - with a direct line to the founders.

We're looking for a Senior Applied Researcher and Team Lead to help shape how our conversational agents are designed, evaluated, and shipped reliably at production scale.



Key Responsibilities

Partner directly with the Applied Research Team Lead to define and evolve team process, technical standards, and the quality bar for agent behavior.
Take real user experience and data through the full arc, from concept to a reliable agent design to a shipped, production-grade product.
Own or share ownership of the standing function of assessing AI tools, models, and providers for reliability and fit.
Raise the technical bar across a team spanning research-leaning grad students to engineers newer to AI, and turn personal expertise into shared tooling and standards the whole team can use.
Operate pragmatically inside current infrastructure constraints while flagging where structural fixes are needed.

We are seeking a visionary and highly influential Principal Software Engineer / Software Architect to define and drive the architectural direction of unified DataOps platform. This is a strategic and hands-on role where you will be responsible for the holistic design of our large-scale, cloud-native solutions, ensuring they are robust, scalable, secure, and maintainable. You will be instrumental in evolving our technology stack, ensuring our architecture supports future business growth and innovation, and mentoring the next generation of technical leaders.

What You'll Do
Define & Own Architecture: Define, evangelize, and own the overall software architecture vision and strategy for unified DataOps platform.

Lead System Design: Lead the design and evolution of complex, large-scale, and highly distributed cloud-native systems on AWS, ensuring high performance, scalability, reliability, and security.

Establish Standards: Establish and enforce architectural standards, best practices, and patterns across all engineering teams.

Strategic Collaboration: Collaborate closely with executive leadership, product management, and engineering teams to translate business strategy into actionable technical roadmaps and architectural solutions.

Hands-on Guidance: Provide hands-on architectural guidance, review critical designs, and contribute to proof-of-concepts or complex coding challenges when necessary.

Risk Mitigation: Proactively identify and mitigate architectural risks, anticipating future technical challenges and designing resilient solutions.

Technical Leadership & Mentorship: Mentor and provide strong technical leadership to senior engineers and other architects, fostering a culture of technical excellence and continuous learning.

Technology & Tooling: Drive technology selection, evaluation, and adoption processes, ensuring alignment with architectural principles and business needs.

Our Professional Services is seeking an Experienced system Engineer We are seeking an Experienced system Engineer to join our team and drive the development of diverse, cutting-edge UAV systems.
If you are looking for a meaningful technological journey filled with multidisciplinary challenges, come and be a part of our story. Key Responsibilities:
* End-to-end development of software- and hardware-intensive UAV systems, from solution definition through technical requirements authoring, integration, testing, and customer delivery.
* Leading complex integration processes, including the integration of products, payloads, and airborne subsystems.
* Defining system -level requirements for various components and authoring detailed specifications and technical documentation.
* Leading cross-functional development and integration efforts across diverse engineering teams, including Airborne Software, C2 (Command & Control) Software, Simulators, QA /Testing, Electronics, and more.