About the role
Responsibilities:
- Work directly with customer product, engineering, operations and customer experience teams to understand workflows, pain points, success metrics and technical constraints.
- Translate customer requirements into working solutions, APIs, data models, integration contracts, implementation plans and acceptance criteria.
- Build and maintain backend services and integrations using Java and Spring Boot for customer-facing and platform workflows.
- Build AI/LLM capabilities in Python, including agent workflows, tool/API calling, evaluation, guardrails, automation and MLOps support.
- Integrate Conversational AI with contact-center/CCaaS systems, CRM, ticketing, identity, knowledge bases and enterprise APIs.
- Work with ElevenLabs for Voice AI, OpenAI for LLM capabilities, and Strands as a decision-making/orchestration layer where appropriate.
- Design secure, observable cloud solutions on AWS, using DynamoDB and PostgreSQL based on data needs. Collaborate on React-based frontend workflows as required.
- Build for production: authentication, authorization, retries, idempotency, rate limits, timeouts, error handling, logging, monitoring, deployment and incident response.
- Design for concurrent customer sessions and latency-sensitive interactions using appropriate multithreading, asynchronous processing, resource limits and backpressure.
- Advance multimodal experiences spanning voice, text and images, including context management, routing, evaluation and graceful failure handling.
- Prototype quickly, validate with customers, iterate on real usage and turn successful prototypes into maintainable production systems.
- Own technical troubleshooting and customer escalations; coordinate with Product and Engineering on platform gaps and reusable capabilities.
- Document architecture decisions and reusable implementation patterns without sacrificing customer-specific needs or platform integrity.
- Customer requirements become working, production-ready solutions with measurable outcomes.
- Integrations and AI workflows are reliable, secure, observable and maintainable.
- Customer issues are diagnosed and resolved quickly with clear communication and effective escalation.
- Solutions meet agreed measures such as resolution/containment, latency, reliability, adoption, satisfaction and operating cost.
- Reusable patterns reduce implementation time without compromising customer requirements or platform integrity.
- Strong hands-on software engineering experience, ideally 4+ years, delivering customer-facing enterprise software into production.
- Mandatory Java competency for backend engineering, preferably Spring Boot, REST APIs, dependency injection, testing, exception handling and service design.
- Mandatory Python competency for AI engineering, automation, LLM integrations, tool calling, evaluation and/or MLOps workflows.
- Hands-on Conversational AI experience, including conversation state, context handling, fallback, escalation and production measurement.
- Experience building APIs and enterprise integrations; familiarity with authentication, webhooks, retries, idempotency, rate limits and event-driven patterns.
- Strong debugging and production-readiness skills across testing, observability, performance, reliability and secure customer-data handling.
- Ability to lead technical discovery, handle ambiguity, explain trade-offs and take ownership from problem definition through deployment.
- Working knowledge of cloud architecture and deployment practices; AWS experience is preferred.
- Consumer-facing CCaaS/contact-center experience across Messaging, Digital AI, IVR, Voice AI, routing and/or agent assist.
- AWS production experience with DynamoDB and PostgreSQL.
- React or another modern frontend framework, sufficient to debug integrations and collaborate full-stack.
- Experience integrating ElevenLabs, OpenAI and/or Strands, or equivalent Voice AI, LLM and agent-orchestration technologies.
- Practical understanding of multimodal AI, concurrency/multithreading and high-volume, low-latency services.
- AI evaluation, prompt/version management, model monitoring, guardrails, human handoff and AI quality measurement.
- Comprehensive Insurance (Life, Health, Accident).
- Flexible Work Model.
- Accelerated learning & non-linear growth.
- Flat organization structure driven by ownership and accountability.
- Opportunity to own and be a part of some of the most innovative and promising AI/SaaS product companies in North America and around the world.
- Accomplished Global Peers - Working with some of the best engineers/professionals globally from the likes of Apple, Amazon, IBM Research, Adobe and other innovative product companies.
- Ability to make a global impact with your work, leading innovations in Conversational AI, Energy/Utilities, ESG, HealthTech, IoT, Risk/Compliance, CyberSecurity, PLM and more.