Main roles and responsibilities:
Partner with business leaders to identify, assess, and prioritize AI and automation opportunities across workflows and processes.
Hands-on creation of scalable AI-enabled workflows and operating models that align with business needs, available tooling, and business systems.
Translate use cases into clear implementation requirements, process definitions, documentation, and success criteria.
Build and maintain AI playbooks, standards, usage guidelines, and best practices for employees and teams.
Lead enablement activities, including onboarding, workshops, training materials, office hours, and internal knowledge sharing.
Drive adoption of approved AI tools and capabilities across the organization, helping teams move from experimentation to sustainable usage.
Collaborate with business stakeholders to ensure AI usage aligns with governance, privacy, security, confidentiality, and compliance requirements.
Establish feedback loops, reporting, and measurable KPIs for AI adoption, productivity gains, and business outcomes.
Monitor external AI trends, vendor capabilities, and emerging practices, and recommend improvements relevant to our company.
Support vendor evaluation, tool rationalization, and the rollout of new AI capabilities where needed.

We are seeking a strategic technical leader to drive the next phase of our engineering evolution. Reporting directly to the VP of R&D, you will carry two core mandates:
Manage one or more engineering teams with a focus on AI development.
Lead AI SDLC transformation efforts across the entire R&D organization.
This is a rare, high-leverage role at the intersection of people leadership, technical craft, and organizational transformation. If you want to define how an entire engineering organization works in the age of AI - and leave a lasting fingerprint on a fast-scaling SaaS platform - this role is for you.
What You'll Do:
Domain Ownership & People Management:
Assume operational leadership for critical R&D domains, including management of engineering teams focusing on AI.
Manage, coach, and grow Team Leads and senior engineers, building leadership depth across your domains.
Own team health, delivery velocity, and engineering quality for every team under your purview.
AI Developer Experience (AI DX):
Lead the transformation of our engineering processes by implementing AI-driven tools, frameworks, and workflows.
Significantly accelerate R&D throughput, optimize developer workflows, and foster an AI-first engineering culture - leading by example.
Drive adoption of agentic coding tools (e.g., Cursor, AI agents) across teams and measure their impact on productivity.
Technical Authority & Governance:
Challenge existing architectural paradigms and introduce innovative, out-of-the-box solutions to complex technical problems.
Mentor engineering teams and raise the bar for AI engineering quality and best practices across R&D.
Strategic Cross-Team Leadership:
Orchestrate complex, cross-functional initiatives that require deep technical alignment across disparate teams.
Manage project delivery, timelines, and execution to ensure seamless cross-functional results.
Architectural Vision:
Define and execute the long-term technical AI roadmap, ensuring high standards of scalability, reliability, observability and engineering excellence across the platform.

We're looking for a business-minded, technically strong leader to lead Business Applications and play a key role in building a more autonomous company. You'll work across the company to unpack complex problems, spot where technology creates real leverage, and lead a team that turns those opportunities into working solutions, from AI agents and automation to custom builds, integrations, and enterprise platforms.
We believe two things matter for every leadership role: leadership that sets the bar for excellence, builds high performing teams, and holds them accountable, and strategy that thinks several years ahead and turns ambitious plans into reality. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role you'll:
Get deep into how teams operate, understanding their goals, economics, workflows, and constraints to identify the highest-leverage opportunities for technology
Build toward a more autonomous by identifying where work can be fundamentally redesigned through agents, AI, and software, then leading the team in making it real
Own problems end-to-end, from framing the problem and shaping the solution through implementation, adoption, and measurable impact
Shape a forward-deployed BizApps model where the team works close to the business, moves quickly, prototypes fast, and shares accountability for results
Lead and grow a strong team that combines business understanding, product thinking, and technical depth, raising the bar for ownership, curiosity, and speed
Build a point of view on where technology creates the most leverage across, then turn that into a portfolio of initiatives you drive from opportunity to measurable impact.

Were looking for an Engineering Team Lead, who will be responsible for the foundational infrastructure framework used by all our engineering teams to build, deploy, and operate AI agents safely in production. We are building the "operating system" for AI, covering agent sessions, memory management, tool orchestration, durable execution, and multi-tenant isolation. You will lead a high-impact team of 5 engineers to create the runtime and platform that defines the future of autonomous enterprise intelligence.
Youll Own:
Agentic Framework Architecture: Designing and building our internal agentic framework, leveraging and integrating industry-standard tools such as LangChain, LangSmith, ADK, and similar ecosystems.
Evaluation and Quality Systems: Building evaluation frameworks and workflows for AI agents, including offline and online evaluations, quality metrics, regression detection, and experimentation infrastructure.
Team Leadership & Mentorship: Leading a squad of 3-4 senior engineers, fostering a culture of technical excellence, and managing end-to-end delivery in a fast-paced environment. You will spend approximately 50% of your time hands-on, architecting core systems and reviewing code, and 50% leading the team, mentoring engineers, and aligning with cross-functional stakeholders.
Observability, Monitoring, and Guardrails: Providing the organization with robust observability capabilities for AI agents, including tracing, logging, monitoring, cost tracking, and safety guardrails to ensure reliable and responsible usage.
Developer Enablement Platforms: Creating APIs, SDKs, and abstractions that enable product teams to easily build, test, and operate agents while adhering to platform standards.
Cross-Language Integrations: Designing integrations and tooling across Python and Java to enable seamless adoption of the AI framework within our broader backend ecosystem.
Youll Solve:
Agent Lifecycle and Orchestration Complexity: Managing agent execution, tool usage, memory, workflows, and failure modes in production-grade systems.
AI System Reliability at Scale: Ensuring agents remain observable, debuggable, and safe as usage scales across teams and products.
Evaluation and Drift Challenges: Detecting quality regressions, model behavior changes, and unintended agent behaviors through robust evaluation and monitoring systems.
Platform Adoption Friction: Balancing flexibility with guardrails so teams can innovate quickly without compromising reliability, security, or cost controls.
Youll Impact:
Company-Wide AI Enablement: Empowering every engineering team to build agent-based solutions faster, with higher quality and confidence.
Foundational AI Infrastructure: Establishing the core frameworks, evaluations, and observability standards that all AI agents will rely on.
AI Safety and Quality Bar: Raising the bar for how AI systems are evaluated, monitored, and governed across the company.

A security company, is building an internal AI capability across the organization: agents that perform real tasks as the organization, with ROI and security assessed at every step. We are looking for a senior engineer who owns this end to end - a hands-on builder who also carries the senior function: setting the technical strategy, making the architecture calls, and being the person leadership trusts on internal AI.
This is not a pure IC build role and not a pure strategy role. You will personally build the flagship systems - production agents, the context layer, the evaluation and safety stack - while also deciding what gets built, in what order, and to what standard. You will work across R&D, IT, Security, BizOps, Customer, Sales, Marketing, People, and Finance, with the AI Transformation Officer owning the business portfolio.
What you'll do - strategy and senior function:
Own the technical strategy for our internal AI transformation: target architecture, model and vendor choices, build-vs-buy calls.
Shape the AI portfolio: which workflows to automate, in what sequence, with what success metrics - and push back when the wrong thing is being built.
Set and enforce the bar on ROI and security for every AI system: cost, adoption, cycle-time impact, access control, and auditability are reviewed per project, not after launch.
Act as the senior technical voice for internal AI: advise leadership, review AI initiatives across the org.
Turn one-off builds into a real internal platform: reusable patterns, shared services, and standards that AI Champions and teams adopt.
Mentor AI Champions; raise the org's practical AI level.
Manage our AI- Champions Community.
Continuously evaluate models, vendors, and frameworks, and keep us agile.
What you'll do - hands-on build:
Personally design, build, deploy, and own the flagship internal agents and AI workflows, from prototype through production.
Build and evolve our AI context layer: connectors, APIs, retrieval services, metadata, identity and authorization, controls, and tool interfaces.
Create safe action tools for agents and infrastructure for agents to work.
Build RAG, tool-calling, structured-output, and multi-step agentic workflows using the right model and architecture for each problem.
Own the production quality bar for what you ship: evaluation datasets and automated checks (accuracy, groundedness, task completion, safety, cost etc.)
Work directly with business owners to map processes, test with users, and drive each pilot to a clear scale-or-stop decision.

we are looking for a R&D Director.
As an R&D Director at Vetric, youll lead multiple engineering teams and their leaders, owning the technical direction, execution, and organizational development of a critical area within our R&D organization.
Youll be responsible for translating company priorities into an effective engineering strategy, building strong teams and leaders, and ensuring we deliver scalable, reliable systems at high velocity.
Youll work closely with R&D leadership and cross-functional stakeholders to shape priorities, drive execution across teams, and continuously improve our engineering organization, architecture, and production excellence.
Responsibilities:
Lead and scale engineering teams and leaders, developing strong Team Leads and engineers while building a culture of ownership, accountability, collaboration, and continuous growth.
Own the engineering strategy and technical direction for your domain, translating business and product priorities into clear technical priorities, architecture decisions, and execution plans.
Drive execution across multiple teams, ensuring effective prioritization, alignment, and delivery of complex initiatives while managing dependencies and removing organizational and technical blockers.
Own production excellence and system reliability, driving high standards around scalability, performance, observability, incident management, and continuous improvement of our production environment.
Drive engineering excellence across the group, establishing and continuously improving standards and practices around architecture, development processes, code quality, and operational readiness.
Own organizational and capacity planning for the group, including team structure, hiring, resource allocation, and developing future technical and managerial leaders.
Partner with stakeholders across the company, including Product, Customer Success, and company leadership, to ensure engineering priorities are aligned with customer needs and broader business objectives.
Drive measurable impact, using data and engineering metrics to evaluate priorities, improve execution, and ensure resources are focused on the areas that create the greatest impact.

We are seeking an experienced Program Manager - Decisioning (Credit Risk) to own, evolve, and execute our risk decisioning products. This role partners closely with ML Engineers , Engineering Leads and Business Stakeholders to transition us from product-specific silos into a generic, high-velocity engine powering Card, BNPL, and emerging products.

Blending strategic oversight with hands-on, rigorous program execution, you will turn complex risk logic into scalable, explainable platforms. Youll own both long-range quarterly planning and sprint execution- defining who we approve, on what terms, and at what expected loss- while ensuring strict alignment with our risk portfolios, regulatory requirements, and long term unit economics. This role requires strong judgment, deep analytical thinking and meticulous detail standards.

As the Program Manager, your mission is to drive an advanced, adaptable decisioning platform that eliminates financial waste and prepares us for its next stage of hyper-growth. You will drive the delivery of core systems that determine how we approve, price, and manage risk-turning complex data into fair, instant, and transparent outcomes for millions of customers.

What Youll Do

Cross-Functional Partnership
Act as the glue in the "Decisioning Triangle," partnering with Business owners, ML Leads and Engineer Leads to operationalize underwriting policies, while taking into account the trade-offs between approval rates, loss, revenue, and customer experience. Partner and balance competing requirements from various business owners (Heads of Card, BNPL, etc.) as well as Compliance, Legal, and Operations to ensure high-quality execution and regulatory integrity.

Hands-On Program Management
Act as an owner for key initiatives, driving the full product lifecycle from discovery and definition through launch, iteration, and performance monitoring. Use data and experimentation to inform decisions and continuously improve outcomes. Identify and remove bottlenecks in the underwriting flow to drive toward high-automation and speed-to-market.

We are seeking an experienced Generative AI Engineer to join our AI squad. This is a unique opportunity to wear multiple hats - serving as both a developer of cutting-edge GenAI solutions and an advisory expert helping organizations transform their AI capabilities. You'll build end-to-end GenAI projects from conception to production while staying at the forefront of this rapidly evolving field.
Key Responsibilities
GenAI Development & Implementation:
End-to-End Development: Build GenAI solutions from POC through production deployment, handling all backend development responsibilities
Client Engagement: Participate in technical discussions with clients, gather requirements, and help translate business visions into feasible technical solutions through presentations and consultations
Backend Development: Design and implement production-grade microservices architectures for GenAI applications using Python
Cloud Implementation: Deploy and manage GenAI solutions across GCP, Azure, and AWS platforms, leveraging cloud-native AI services
Cross-functional Collaboration: Work closely with project managers, full-stack developers, and Power Automate teams to deliver complete solutions
System Evaluation: Assess and optimize production-grade GenAI systems for performance, scalability, and reliability
Continuous Learning & Innovation:
Technology Scouting: Continuously explore and evaluate new GenAI models, frameworks, and techniques as they emerge
Best Practices Development: Establish and refine methodologies for GenAI solution development and deployment

Were looking for a highly motivated AI Developer to help design, build, and deploy intelligent agentic systems across our product ecosystem. In this role, you'll work at the intersection of machine learning, backend systems, and modern frontend technologies to deliver AI-first features that feel magical to users.

This is a hands-on, cross-functional role ideal for engineers who love building full-fledged features-from data pipelines and LLM orchestration to intuitive UI experiences-with a strong product mindset.

Responsibilities:
AI Agent Design & Integration
Design and implement autonomous or semi-autonomous agents using LLMs (e.g., OpenAI, Anthropic, open-source models).
Work with prompt engineering, RAG pipelines, and tool/plugin integrations to enable agents to interact with internal and external systems.
Build scalable agent runtimes and orchestration layers (e.g., LangChain, Semantic Kernel, ReAct-based agents).
Fullstack Product Development
Own full-stack features end-to-end: from backend APIs and data models to React-based frontend interfaces.
Integrate AI/agent capabilities into customer-facing products with clean UX and measurable performance.
Collaborate closely with design, product, and data teams to bring ideas from concept to production.
Systems & Infrastructure
Build and maintain backend services and pipelines that support AI agents, including vector search, embeddings, function calling, and observability.
Optimize inference flows for performance and cost, potentially using streaming, caching, or local model inference.
Ensure systems are secure, reliable, and compliant with InfoSec standards.
Experimentation & Continuous Improvement
Rapidly prototype and iterate on new AI capabilities and user experiences.
Analyze performance and usage metrics to drive product and model improvements.
Stay up to date with the evolving AI toolchain and emerging agent architectures.