Principal Software Engineer building next - gen AI CX tools for TTEC Digital. Collaborating with teams to solve complex engineering problems in a startup - like environment.
About the role
- Engineering Technical Lead at TTEC Digital responsible for building AI CX tools in a startup environment. Leading teams to create innovative solutions for major brands across the globe.
Responsibilities
- Lead developer role, three specialization tracks. We build voice, desktop, intelligence, and AI combined into a single real-time platform — event-driven, high-throughput, low-latency.
- A tech lead here is a player-coach — you write the hardest code in the squad, and you lead it.
- You'll build Go services on the event bus, AI/ML services and pipelines, or connector frameworks to CCaaS/CRM/telephony — most engineers here end up touching more than one.
- This is a startup environment on a fast train: 1-week sprints, Friday demos, fail fast and move forward.
- Services on the event bus (NATS-class) · high-throughput transactional data models and WebSocket backends
- Your track's slice — AI/ML pipelines (RAG, streaming inference, eval) or connectors (CCaaS/CTI, CRM, SIP/RTP) or core platform services
- Your latency budget · your committed timelines.
Requirements
- 9+ years hands-on; same language bar (HIGH++ Go, 3+ languages) and same AI, debugging, and velocity bar as the Senior Software Engineer role —** you must out-code the squad you lead.**** **
- Has led a squad and shipped a hard real-time or platform product end-to-end, on committed timelines.
- Sets patterns by shipping them; owns the code-review bar and raises the engineers around you.
- Owns delivery — moves blocked work, doesn't just report it. Show-me mentality: your squad demos working software every Friday.
- Keeps the respect of senior engineers through technical credibility, and manages change without drama — priorities and tech will shift under you.
- Event-driven systems in production (NATS / Kafka / Redpanda-class) — you think in pub/sub. Heavy WebSocket, real-time, low-latency.
- Mid-tier or better hands-on AI experience in the code and product — you've built with LLM APIs, embeddings, RAG, or model serving, not just chatted with a bot. And you use AI-assisted development daily to multiply your velocity.
- Strong ++ for data graph/knowledge graph background, or hands-on AI/ML model experience (training, serving, eval).
- Efficiency in development — we deal in speed. You ship clean code fast, unblock yourself, and your estimates hold.
- A master debugger — you read unfamiliar code, a stack trace, or a flaky partner API and see it; you know where the breakpoint goes.
- GCP preferred. Voice (SIP/RTP/SIPREC), CCaaS/CTI, or desktop-adjacent experience a strong plus depending on track.
- Track emphasis:
- Backend/Platform: data models, event bus, plugin runtime.
- AI/ML: deeper Python, production GenAI/NLU, streaming inference, eval frameworks, RAG.
- Integrations: CCaaS/CTI platforms (Genesys, Amazon Connect, NICE, Five9), CRM connectors, SIP/RTP, fault-tolerant connector design. **
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