🕒 6 days ago
Lead the team responsible for building secure, isolated environments for AI agents, focusing on people management and technical architecture.
Engineering Tech Lead
📅 Jul 11
GoAI/MLEvent-driven SystemsDebugging
📜 Description
- Lead developer role with three specialization tracks in voice, desktop, intelligence, and AI.
- Act as a player-coach, writing the hardest code and guiding the squad.
- Build Go services on the event bus and AI/ML services and pipelines.
- Work in a fast-paced startup environment with 1-week sprints and Friday demos.
- Own services on the event bus and manage high-throughput transactional data models.
🛠️ Requirements
- You consider yourself exceptional — and can show it.
- Self-starter, hacker, grit, loves to learn, loves winning.
- You demonstrate ideas easily: a working prototype beats a slide deck every time.
- You understand requirements and stay locked on them — we work with all-new technology constantly, and you don't get wrapped around shiny objects
- You evaluate fast, adopt what earns it, and keep shipping. Fail fast, move forward. A team player who makes and hits committed timelines.
Full job description
At TTEC Digital, we coach clients to ensure their employees feel valued, and fully supported, because an amazing customer experience is an employee first process. Our vision is the same, a place where employees know they can thrive.
TTEC Digital seeks an Engineering Technical Lead to join our team. This role is a full-time and fully remote opportunity!
The work:
We’re an innovation group inside TTEC (NASDAQ: TTEC), building the next generation of AI CX tools — automated QA, conversational analytics, knowledge assist, and agentic automation — for the world’s biggest brands and the millions of customers they serve. We move like an early-stage startup, backed by the scale, distribution, and enterprise client base of a company that’s been obsessed with customer experience since 1982.
This is the rare seat where getting in early actually matters at scale. TTEC is a public company at an AI inflection point. Ship the right products into thousands of live enterprise deployments and you don’t just move a metric — you move the trajectory of the company and the value of the stock. The leverage is real, and the work compounds.
Who we hire — the DNA
-
Self-starters and do-ers with grit — hackers in the best sense, with a startup mentality and a show-me bias: working software over slides, prototypes over proposals.
-
Want to learn, love new technology. This platform is built on the latest technology, and that technology changes and advances monthly. You adapt to change quickly — new tools, new models, new priorities — without drama.
-
Master debuggers and problem solvers. You love solving complex problems, you think outside the box, and you multitask across domains without losing the thread.
-
AI-native. You work with AI on all levels — you understand the technology around you (LLMs, SLMs, RAG, knowledge graphs, agents, training, eval) and you use AI tools daily to exponentially increase your velocity.
-
Distributed-systems literate. High-efficiency, event-driven, low-latency systems are our world; you understand what that demands.
-
Innovators who ship. You demonstrate ideas easily, fail fast, and move forward. You make committed timelines and hit them.
-
You consider yourself exceptional — and you like winning. So do we.
No one will have everything in this description. We're looking for well-rounded, smart people who move fast.
What You Will Do:
The role:
What you'll own:
Who you are:
What You Will Bring:
-
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.
Similar jobs
Search more Engineering Manager jobs🕒 6 days ago
Lead the engineering team responsible for designing and managing a Kubernetes product, focusing on people development and technical excellence in a hands-on role.
🕒 6 days ago
Lead the team responsible for transforming hardware into operational clusters, focusing on automation and reducing time to acceptance for datacenter deployments.
Engineering Manager, Provider Ecosystem
🕒 2 days ago
OpenRouter👥 51 - 200 employees🏢 Computer Software
🕒 2 days ago
Lead the Provider Ecosystem team at OpenRouter, managing engineering talent and driving the integration of diverse AI models and endpoints while ensuring high-quality performance.
🕒 4 days ago
Lead a team of AI Tutors to ensure high-quality training data and evaluations for SpaceXAI's models, while driving operational excellence and continuous improvement.