Job description

ABOUT GIGA Giga has recently raised a $61M Series A and is working with Fortune 500 customers to deploy the next generation of customer experience - real-time AI agents that can understand emotion, resolve issues instantly, and scale across the world's largest enterprises. Industry leaders like DoorDash trust Giga with their most complex support and operations workflows across voice, chat, and email, in high-stakes regulated environments where accuracy and compliance matter. We're at an exciting inflection point. While we've found real commercial success, our ambitions are larger: to become the go-to AI platform for all enterprise automation, powered by our voice superintelligence. The work affects millions of people every day, and our team has the autonomy to make true impact - with brilliant founders, a clear path forward, and the kind of momentum that defines generational companies. If being part of that resonates with you, we'd love to hear from you! - Voice AI startup Giga raises $61M Series A fortune.com - DoorDash and Giga Partnership linkedin.com THE ROLE We're hiring Senior Forward Deployed Engineers as we scale our FDE organization. This is a senior individual contributor role — for engineers who want to stay engineers: you'll be the technical anchor of a pod of FDEs, own our most complex enterprise deployments, and build the tooling and practices that make every deployment after yours faster. Your impact spans the org — the systems, patterns, and standards you build become how every pod operates. You'll operate with real autonomy — architecture decisions, live production debugging, direct engagement with customer engineering leadership. No direct reports: your leadership shows up in code, design reviews, the engineers you level up, and an FDE org that gets epsilon better every day because you're in it. WHAT YOU'LL DO - Own the hardest deployments end-to-end. Architect agent systems for Fortune 500 environments, build enterprise integrations, and make the scope/speed/quality trade-off calls that ship production agents on aggressive timelines. - Be the technical anchor of your pod. Set the engineering bar through design and code reviews, mentor FDE I/II engineers, and serve as the escalation point for the hardest live issues — real-time voice latency, telephony edge cases, integration failures, agent quality regressions. - Build leverage, not just deployments. Create the eval harnesses, deployment tooling, debugging infrastructure, and reusable patterns that compound across every pod. - Drive the product feedback loop. Turn deployment learnings into prototypes and concrete asks, and work directly with core engineering to land platform improvements. - Face the customer as a technical peer. Run architecture discussions with customer engineering leaders and be the person they trust when production breaks. WHO YOU ARE - Strong engineering foundation. 5+ years of production software engineering, ideally at companies known for high engineering bars. You've shipped and operated real systems at scale. - Deep on the stack. Expert in Python, APIs, cloud infrastructure, CI/CD. You debug distributed systems under pressure and learn new integration surfaces quickly. - AI-native. Hands-on with LLM agent systems — orchestration, tool calling, evals, context engineering — and the latency budgets real-time voice demands (or the chops to ramp fast). - Customer-tolerant. You can sit across from enterprise stakeholders, translate ambiguity into a plan, and stay calm when production is on fire in front of them. - High agency. You find the highest-leverage problem and go, with limited or no guidance. NICE TO HAVE - Prior forward deployed / solutions engineering at an AI or enterprise software company - Real-time voice or conversational AI experience - Early-stage startup experience PERKS & BENEFITS - Competitive base + bonus + equity - Catered lunch daily - Dinner stipend - $500/month wellness & commuter benefit (gym, fitness classes, mental health) - 401(k) plan - Medical, dental, and vision coverage Giga is an equal opportunity employer. We're committed to providing equal employment opportunities regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law.

Requirements

Must-haves

Build leverage, not just deployments. Create the eval harnesses, deployment tooling, debugging infrastructure, and reusable patterns that compound across every pod.
Drive the product feedback loop. Turn deployment learnings into prototypes and concrete asks, and work directly with core engineering to land platform improvements.
Face the customer as a technical peer. Run architecture discussions with customer engineering leaders and be the person they trust when production breaks.
Strong engineering foundation. 5+ years of production software engineering, ideally at companies known for high engineering bars. You've shipped and operated real systems at scale.
Deep on the stack. Expert in Python, APIs, cloud infrastructure, CI/CD. You debug distributed systems under pressure and learn new integration surfaces quickly.
AI-native. Hands-on with LLM agent systems — orchestration, tool calling, evals, context engineering — and the latency budgets real-time voice demands (or the chops to ramp fast).
Customer-tolerant. You can sit across from enterprise stakeholders, translate ambiguity into a plan, and stay calm when production is on fire in front of them.
High agency. You find the highest-leverage problem and go, with limited or no guidance.

Nice-to-haves

Prior forward deployed / solutions engineering at an AI or enterprise software company
Real-time voice or conversational AI experience
Early-stage startup experience

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aigopythonci/cdllm

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Wellness