Hi, I'm Raj, and I'm the Engineering Leader for Jane AI alongside my colleague, Thibaut. We're hiring a Senior or Staff Developer to join our team. Jane AI is a new team operating inside Jane as a startup. Our mission is to transform Jane into a lasting AI-first offering that leads our industry, in the shared pursuit of "helping the helpers." We're running three connected workstreams: - An agentic platform in Rails. A true SDK with tool use, orchestration, and context management that empowers teams across Jane to create AI-powered capabilities. Not a wrapper around an LLM. - Jane Companion. An AI-first, mobile-first product that rethinks practice management from scratch. What does a practitioner's day look like when every interaction is designed for AI from the ground up? A cohesive chat experience that connects everything in Jane. - Connective infrastructure. A capability built once is available everywhere: in the mobile app, on the phone, in the clinic's workflow. Intelligence flows across surfaces. Our new Senior/Staff Full Stack Engineer will work across all three. We need someone who can own architecture decisions, solve hard problems around performance and help the team grow as we continue to discover new opportunities. If you're excited about building something new at the intersection of full stack engineering and AI, we'd love to talk. What Experience We Need - 7+ years as a Software Engineer. We're looking for a strong senior or someone early in their staff journey. - Strong across or open to working with Ruby/Rails, TypeScript, and if you have experience with React Native, that'd be helpful too. - Comfortable working the full stack, not just a preferred corner of it. - Builder of your own tools. Automates tedious work instinctively, writes scripts and internal tooling to create leverage for the team. Experience building AI in production (agents, LLM orchestration, real user-facing features) is a significant bonus. - Self-directed. Sees what needs doing and does it. Comfortable with ambiguity. Doesn't wait to be told. - You've shipped something from scratch (product, company, side project) that people actually used. - Bias toward action. Ships and iterates rather than waiting for perfection. - Security-conscious. Understands why this matters when handling sensitive health data. More About Jane Jane is practice management software loved by allied health practitioners, from physiotherapists and counsellors to chiropractors and massage therapists. We grew entirely through word of mouth. No sales team. Just a product people loved enough to tell their colleagues about. Today, Jane supports over 65,000 clinics in 60 countries and we have over 1,000 new clinics joining Jane every month. We're profitable, north of $1.8B in valuation and remote-first. That combination, organic growth, real scale, real revenue, is rarer than it sounds. We're now in the middle of our most significant chapter yet. AI is changing what software can do, and we're leaning in hard, both in how our team works and in what we build for our customers. A note on pace Jane AI in a different season than most teams. We're chasing product-market fit with urgency. The pace is faster, the ambiguity is higher, and we lean in when it counts. It's not forever, but it's where we are right now. If you're energized by that kind of environment, you'll thrive here. The setup We're remote and async-first. Jane AI operates with autonomy, our own roadmap, our own priorities, our own ways to get work done, while staying connected to Jane for shared services and collaboration. We're flexible on level. What matters most is whether you can contribute meaningfully from day one. What we offer - Competitive compensation. This role has an annual base salary range of $180,000 to $280,000, plus equity through our JSOP (Jane Stock Options Plan). Our stock has grown 11x over the past six years, and team members have had the opportunity to exercise their options three times in that same period. In May 2025, Jane was valued at $1.8B, and with the recent backing of TCV, we have ambitious growth plans ahead. - Access to real problems. If you've felt constrained by the ceiling in previous roles, this is different. You'll work on hard problems, talk directly to customers, and see your work make a real impact. - Benefits. Full healthcare coverage and flexible time off.

The AI Platform Engineer is a hands-on technical leader responsible for the technical strategy, architecture, and delivery of key AI platform capabilities, including Generative and Agentic AI. This role guides reusable patterns and technology architecture, drives adoption of next-generation platforms, and reduces complexity while increasing business value. The Engineer partners closely with engineering managers and stakeholders to translate requirements into a practical technical roadmap and leads a small pod/team through execution with a strong focus on reliability, security-by-design, and developer experience. Responsibilities - Assist with the design and implementation of a unified AI platform, assisting in critical build-versus-buy recommendations for components such as Agent Engines, MCP Servers, AI enabled Enterprise Search, and Agentic Orchestration - Provide options analysis and estimates based on high-level requirements; drive technical direction for platform designs and technology architecture. - Define and standardize “paved road” patterns that accelerate product teams from experimentation to production. - Build and improve underlying platform tools to reduce lead time and improve developer usability and consistency across teams. - Embed “security-by-design” guardrails into the platform, including least-privilege IAM models, automated guardrails, and compliance monitoring for AI data privacy. - Design for reliability and ensure stable operations through monitoring, troubleshooting, and continuous improvement, support incident response practices and long-term remediation. - Design and implement the ADLC (Agentic Development Life Cycle) process to register all agents and tools - Design and implement automated governance processes to secure agents, MCP servers, and LLMs. - Act as a coach/mentor to engineers through high-standard code reviews, best practices, and technical guidance. - Partner with engineering management and stakeholders to translate requirements into technical roadmaps and serve as a bridge between data science teams and core infrastructure. Qualifications - 4+ years of Cloud engineering experience preferred - Demonstrated competency of the Agent Development Kit (ADK) and orchestration patterns like sequential, parallel, and dynamic routing. - Understanding of the Model Context Protocol (MCP) and Agent-to-Agent (A2A) protocols for cross-platform interoperability (e.g., Salesforce Agentforce, ServiceNow). - Strong proficiency in Python or another language (e.g., Go, Java, Rust, Bash). - Experience with infrastructure automation (Terraform or similar) - Mastery of Google Cloud Platform for CaaS or PaaS workloads, including VPC Service Controls for protection of sensitive data - Demonstrated ability to guide architecture, produce estimates, and execute implementations while minimizing risk to production systems. What Is Expected of You and Others at This Level - Serve as a hands-on technical engineer who helps set direction for designs and technology architecture and drives adoption of modern patterns. - Mentor and level-up engineers through coaching, code review, and reusable best practices. - Deliver scalable platform capabilities that standardize the AI lifecycle and improve speed-to-production with embedded guardrails. Anticipated salary range: $94,900 - $135,600 Bonus eligible: No Benefits: Cardinal Health offers a wide variety of benefits and programs to support health and well-being. - Medical, dental and vision coverage - Paid time off plan - Health savings account (HSA) - 401k savings plan - Access to wages before pay day with myFlexPay - Flexible spending accounts (FSAs) - Short- and long-term disability coverage - Work-Life resources - Paid parental leave - Healthy lifestyle programs Application window anticipated to close: 4/27/2026 *if interested in opportunity, please submit application as soon as possible. The salary range listed is an estimate. Pay at Cardinal Health is determined by multiple factors including, but not limited to, a candidate’s geographical location, relevant education, experience and skills and an evaluation of internal pay equity. Candidates who are back-to-work, people with disabilities, without a college degree, and Veterans are encouraged to apply. Cardinal Health supports an inclusive workplace that values diversity of thought, experience and background. We celebrate the power of our differences to create better solutions for our customers by ensuring employees can be their authentic selves each day. Cardinal Health is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, ancestry, age, physical or mental disability, sex, sexual orientation, gender identity/expression, pregnancy, veteran status, marital status, creed, status with regard to public assistance, genetic status or any other status protected by federal, state or local law. To read and review this privacy notice click here

Senior AI Engineer (Agentic Systems / LLMs / Python) · LATAM - Location: Anywhere in LATAM - Job Type: Remote - Project: Fintech Conversational AI Platform - Time Zone: Flexible within LATAM - English Level: B2 / C1 _______________________________________________ Disclaimer – Must read: Commitment & Focus This role requires full-time dedication, with clear priority given to Darwoft projects during the established working hours.It is not compatible with other full-time professional engagements.Any additional professional activities must be disclosed in advance and must not interfere with the responsibilities or working hours of this role. Get to Know Us At Darwoft, we create software that drives real change. But we're more than just tech — we're people first. We believe in building human-centered digital experiences and having fun while we do it. Our team is curious, passionate, and always growing. Based in Latin America, we partner with companies worldwide to develop innovative solutions with purpose. We work remotely, collaboratively, and with a strong sense of community — always embracing continuous learning, adaptability, and real impact. About the Role We're looking for a Senior AI Engineer to join a high-impact fintech project focused on building next-generation conversational AI systems. This is not a traditional chatbot role. You'll be working on production-grade agentic systems, evolving AI from simple interactions into autonomous, multi-agent architectures capable of reasoning, planning, and executing complex workflows across critical business domains. You'll operate close to the core AI strategy, collaborating with product and engineering teams to bring intelligent systems into real-world production environments — with direct impact on thousands of users. What You'll Be Doing - Design, build, and deploy stateful AI agents using Python and modern agentic frameworks (LangGraph, CrewAI, etc.) - Develop multi-agent systems capable of handling complex, multi-step workflows with reasoning and planning - Implement and optimize RAG pipelines using vector databases for accurate and grounded outputs - Integrate AI agents into core product infrastructure (APIs, internal services, business workflows) - Build LLMOps capabilities, including monitoring, tracing, and observability of agent behavior (reasoning paths, latency, tool usage) - Design advanced evaluation pipelines (evals-as-code) using techniques like LLM-as-a-judge, semantic similarity, and adversarial testing - Optimize systems for performance and cost efficiency (prompt optimization, caching, model routing) - Ensure production readiness through CI/CD pipelines, containerization (Docker/Kubernetes), and system reliability practices - Collaborate with cross-functional teams to translate business needs into scalable AI solutions - Mentor and contribute to best practices in AI engineering and software craftsmanship What You Bring - 7+ years of experience in software engineering - 2+ years building AI / Generative AI systems in production - Strong proficiency in Python - Hands-on experience with LLM frameworks and APIs (OpenAI, LangChain, LlamaIndex, CrewAI, or similar) - Proven experience designing agentic systems (multi-agent workflows, memory/state management) - Solid experience with RAG architectures and vector databases - Strong understanding of software engineering fundamentals (Git, testing, CI/CD) - Experience integrating AI into real production environments, not just prototypes - Ability to translate business problems into scalable technical solutions - Strong communication skills in a remote, English-speaking environment Nice to Have - Experience in fintech, payments, fraud, or financial platforms - Experience with LLMOps tools (LangSmith, Arize, Weights & Biases, etc.) - Experience with evaluation frameworks and benchmarking for LLM systems - Background in cost optimization of AI systems at scale - Contributions to open-source or public AI projects - Experience working in high-growth, fast-paced environments What Darwoft Offers - Contractor agreement with payment in USD - 100% remote work - Argentina's public holidays - English classes - Referral program - Access to learning platforms Explore this and other opportunities at: www.darwoft.com/careers

About the role This is not a role where you will bolt AI onto an existing product as an afterthought. SqlDBM is rebuilding core workflows around AI — from how data architects design schemas to how engineers validate changes to how governance teams maintain compliance across enterprise environments. You will work at the intersection of .NET backend engineering and applied AI — building the systems that make AI a first-class, reliable, enterprise-grade capability inside one of the most technically demanding categories in data infrastructure. This role sits inside our dedicated AI group and reports directly to senior leadership. You will have a short line to product, architecture, and business decisions — no layers, no queue. The team is small by design, moves fast, and has direct visibility into enterprise customer needs. What makes this role different You are not building a chatbot. You are building AI infrastructure for enterprise data teams — systems that understand schema context, generate governed artifacts, and integrate into the workflows of the world's most sophisticated engineering organizations. The problems are hard. The customers are demanding. The work is meaningful. What you'll do You will own and extend the backend systems that power SqlDBM's AI capabilities. Specific areas include: - AI-assisted data modeling workflows — backend services that allow users to describe their data needs in natural language and receive accurate, governed schema output - Context-aware intelligence — systems that use the full richness of a user's data model, naming standards, and governance rules to produce AI output that is specific to their environment, not generic - Automated documentation and metadata generation — AI pipelines that analyze existing schemas and produce accurate, consistent business documentation at scale - Integration with enterprise AI ecosystems — API layers that allow external AI agents and tools to call SqlDBM as a trusted source of schema context - Consumption tracking and orchestration — backend infrastructure that manages AI request routing, model selection, cost optimization, and usage metering - Governance-aware AI workflows — systems that embed approval, validation, and compliance logic into AI-generated outputs before they reach production - MCP server development — building and extending SqlDBM's Model Context Protocol server so that external AI agents and LLM-based tools can use SqlDBM as a trusted, real-time schema authority - Tech Stack includes: C# / .NET AWS PostgreSQL Redis REST APIs LLM Integration MCP Microservices Our backend is built on modern .NET with a microservices architecture deployed on AWS. AI capabilities are built on top of major LLM providers via API, with proprietary prompt engineering, context management, and output validation layers that are core intellectual property of the platform. Qualifications - 5+ years of backend engineering experience with C# and .NET - Strong understanding of REST API design and asynchronous service architectures - Experience integrating with external APIs and managing complex data pipelines - Comfort working with LLMs via API — understanding of prompt construction, context management, token economics, and output validation - Experience building systems that handle variable, structured data — schemas, metadata, or similar - Strong engineering fundamentals — testing, code review, system design, observability - Ability to work independently in a remote-first, fast-moving engineering team Strong Plus - Experience with data modeling, database design, or data engineering tooling - Familiarity with enterprise data platforms — Snowflake, Databricks, dbt, or similar - Background building developer tools or platforms used by technical teams - Experience with agentic AI workflows, tool-use patterns, or AI infrastructure - Knowledge of semantic layer concepts, ontologies, or structured metadata systems - Familiarity with Model Context Protocol (MCP) — building or consuming MCP servers in agentic AI architectures What We Offer - Competitive base salary and equity in a profitable, growing company - Fully remote — work from anywhere - Direct impact on product direction — small team, no layers, your work ships to enterprise customers - Work on genuinely hard technical problems at the frontier of AI and enterprise data infrastructure - Collaborative, engineering-driven culture that moves fast and trusts its people - Benefits - comprehensive insurance coverage for employees and their dependents — including medical, dental, vision, life, and both short- and long-term disability, parental leave, an employer-sponsored 401(k) retirement plan, and stock options. Why now SqlDBM is at an inflection point. We have enterprise customers, a profitable business, and a product that is becoming something significantly more powerful. The engineers who join now will shape what that means and build the systems that define the next chapter of data architecture tooling.