Orbio AI

Position Overview

Orbio is looking for a Senior Backend/Full-Stack Engineer (primarily backend) to help build our conversational, agentic AI platform, integrations and APIs. You'll architect and scale production-grade systems supporting hiring, onboarding, and employee experiences in real enterprise environments, working with LLMs and autonomous agents as part of the stack.

What You'll Do

1. Build and scale production-grade backend systems
2. Implement end-to-end features
3. Make pragmatic technical decisions balancing innovation with reliability
4. Collaborate with product and business stakeholders
5. Ship reliable software that performs at scale

Technical Skills

Backend

1. Strong Python expertise: async programming, API development, real-time ASGI (Django/Channels)
2. Testing, logging, monitoring, performance optimization
3. Data storage (SQL and NoSQL) and async message queues (Celery + RabbitMQ / Redis)
4. High-throughput, low-latency systems
5. Production-grade application development

Full-Stack & DevOps

1. JavaScript frameworks (React preferred)
2. CI/CD pipelines and cloud platforms
3. Deploying and scaling systems in production

AI (working knowledge, willingness to go deeper)

1. Basic understanding of LLMs: prompt engineering, RAG, function calling
2. Familiarity with agentic patterns and orchestration
3. Awareness of LLM cost, guardrails, and evaluation
4. Exposure to conversational/voice AI (STT/TTS, telephony) a plus

What Success Looks Like at Orbio

1. Core backend and agentic systems run reliably in production at enterprise scale
2. AI workflows meaningfully reduce operational friction for customer teams
3. The platform compounds: new deployments get faster and more robust over time
4. Technical foundations support autonomy, observability, and safe decision-making
5. Engineering velocity stays high without sacrificing reliability

Culture at Orbio

Orbio is a high-bar, high-intensity environment. We optimize for impact, speed, and ownership — not comfort.

We operate as one team, with a flat structure and extreme ownership. We ship fast, learn from production, and challenge each other directly because we care about building something that lasts. Titles matter less than outcomes. Customers come first. Momentum matters.

We're looking for an experienced AI Governance & Compliance Engineer to ensure that AI systems remain compliant, auditable, and trustworthy across global regions including EMEA, US, LATAM, and APAC. This role bridges Legal, Engineering, and Security, translating regulatory needs into technical implementation and building the compliance infrastructure that supports confident operations with regulators and enterprise clients.

🎯 Responsibilities

1. Monitor regulatory requirements across multiple regions, including early identification of relevant changes affecting AI systems
2. Translate legal interpretations into actionable technical requirements for engineering teams
3. Advise engineering on compliance features such as monitoring, logging, audit trails, human oversight, and risk classification
4. Design and maintain AI compliance dashboards and metrics, including human-in-the-loop measurements
5. Define data sources, logic, and limitations for compliance and risk reporting
6. Conduct AI risk and impact assessments aligned with frameworks like ISO/IEC 42001 and the EU AI Act
7. Keep AI system documentation up to date, supporting legal on assessing AI risk tiers
8. Own technical compliance with data privacy regulations such as GDPR, CCPA/CPRA, LGPD, and PIPL
9. Support data mapping, DPIAs, and privacy-by-design reviews
10. Act as the technical liaison between Engineering/Product, Legal, Security, and enterprise clients—handling questionnaires, due diligence, and compliance reporting

🛠️ Requirements

1. Strong working knowledge of AI regulations and frameworks, including the EU AI Act, ISO/IEC 42001, NIST AI RMF, and regional equivalents
2. Experience translating legal and regulatory language into concrete technical requirements
3. Skilled at monitoring regulatory landscapes across global regions
4. Hands-on engineering experience covering system architecture, code, data flows, and AI model behavior
5. Able to advise on compliance features for engineering teams
6. Sound judgment on when to escalate ambiguous issues to Legal
7. Proficient with AI tools for research, drafting, and analysis
8. Capable of designing and maintaining compliance dashboards and risk assessments
9. Experience in data privacy compliance (GDPR, CCPA/CPRA, LGPD, PIPL) and privacy-by-design practices
10. Strong communication and cross-functional collaboration skills, including working closely with Enterprise clients

🧭 What Success Looks Like

1. AI systems always remain audit-ready and compliant across all covered regions
2. Engineering ships critical compliance features without slowing product development
3. Compliance dashboards provide clear and trustworthy risk visibility for stakeholders
4. Regulatory updates are proactively flagged and addressed
5. Enterprise clients trust and understand the responsible AI posture due to clear and well-prepared compliance documentation

🌟 Team Culture

1. High-impact, fast-paced environment focused on speed, ownership, and real-world results
2. Flat structure promoting direct communication and extreme ownership
3. Collaborative approach with all team members prioritizing customer outcomes and momentum

We're looking for an experienced AI Sales Engineer to lead the technical aspect of enterprise sales cycles, acting as the vital link between clients and advanced AI solutions.

🎯 Responsibilities

1. Lead technical sales cycles end-to-end, from discovery to close
2. Address challenging technical questions and connect capabilities to business outcomes
3. Respond to RFPs, RFIs, and security/compliance questionnaires
4. Coordinate input across Security, Legal, and Engineering on complex deals
5. Prepare technical proposals, solution architecture diagrams, one-pagers, and presentations
6. Communicate technology architecture and data security confidently
7. Demonstrate depth in AI-specific risks and governance
8. Apply knowledge of regulatory/compliance frameworks (e.g., GDPR, SOC 2)
9. Translate compliance requirements into clear communications that reassure clients
10. Design and configure tailored product demonstrations for specific use cases
11. Plan and facilitate technical workshops and discovery sessions
12. Run proof-of-concept engagements with client stakeholders
13. Collect and document business requirements, pain points, and integration needs
14. Translate findings into structured briefs for the Delivery team
15. Serve as the voice of the customer internally with Sales, Product, and Engineering
16. Relay market feedback to influence product roadmap
17. Support the launch of new features

🛠️ Requirements

1. Professional fluency in English and Spanish
2. Proven experience in technical sales engineering, preferably with enterprise clients
3. Strong understanding of technology architecture and data security
4. Experience with AI-specific risk, governance, and compliance standards
5. Ability to prepare clear technical documentation and deliver compelling presentations
6. Background in facilitating technical workshops, demos, and proof-of-concept sessions
7. Excellent communication and cross-functional collaboration skills

➕ Nice to have

1. Fluency in French, Portuguese, or Italian

🌟 What Success Looks Like

1. Prospects move through the sales cycle with technical confidence and no unresolved blockers
2. RFPs, security questionnaires, and compliance reviews are handled accurately and on time
3. Demos and workshops clearly connect product capabilities to each client's real use case
4. Delivery teams receive clear, well-scoped requirements from pre-sales handoffs
5. Product and roadmap decisions are informed by real client and market feedback

💡 Team Culture

1. High-performance, fast-paced environment focused on impact, speed, and ownership
2. Flat structure with emphasis on extreme ownership and collaboration
3. Environment prioritizes outcomes, direct feedback, and customer-first mentality
4. Driven by momentum and real-world results

We're looking for a driven Forward Deployed Engineer / AI Solutions Engineer (Field Engineer) to bridge technical and operational needs, ensuring AI systems create real value for customers from day one.

🎯 Responsibilities

1. Act as the technical bridge between customers and internal teams, driving solutions that deliver immediate, measurable outcomes
2. Work directly with customer teams to deeply understand workflows and define success criteria for system deployment
3. Configure, deploy, and customize AI solutions to optimize enterprise customer processes
4. Serve as a trusted technical advisor in the field—building, problem-solving, and ensuring accountability for results
5. Translate operational goals into technical workflows to improve speed, quality, and scalability
6. Own the technical deployment lifecycle, focusing on reducing time from sale to value
7. Partner with Deployment Strategists to deliver clear customer impact, not just successful launches
8. Transform effective customer solutions into reusable modules and playbooks to accelerate future deployments
9. Relay insights from deployments back to Product Engineering to drive continuous product improvement

🛠️ Requirements

1. Strong engineering fundamentals with ability to deliver production-grade systems quickly
2. Direct experience engaging with customers (field engineering, consulting, or solutions roles)
3. Ability to move between high-level problem definition and hands-on debugging
4. Experience with modern technology stacks (APIs, cloud, frontend/backend development)
5. Fluent in English and Spanish; additional languages are a plus
6. Demonstrated ownership mentality and comfort working in ambiguous, high-intensity environments

➕ Nice to have

1. Experience deploying AI systems in production environments

🌟 What Success Looks Like

1. Customers realize value rapidly post-deployment with noticeable efficiency or speed gains
2. Core workflows are effectively re-engineered with AI, driving measurable ROI
3. Solutions are stable at scale and trusted in daily customer operations
4. Technical solutions are reusable and accelerate onboarding of new customers
5. Continuous product improvement based on structured field feedback