Full Stack Engineer, AI Systems, Artificial Intelligence

TTEC

Full Stack Engineer developing AI Systems and designing workflows. Building production-grade features in a fully remote role.

Posted 7/10/2026full-timeRemote • California • 🇺🇸 United StatesMid-LevelSenior💰 $140,000 - $190,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Full Stack Engineering with a focus on Artificial Intelligence integrations, system design, and API architecture. Proven ability to lead features from concept to production in dynamic environments while ensuring system reliability and performance.

Highest-signal resume keywords

Full Stack EngineeringArtificial Intelligence ExperienceSystem DesignAPI ArchitectureLLMs Integration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Frontend DevelopmentBackend DevelopmentAI IntegrationSystem DesignAPI DevelopmentReal-Time AI InteractionsObservability ImprovementFailure Recovery MechanismsStreaming Data HandlingPragmatic Engineering Decisions

Soft Skills

Strong OwnershipAbility to Handle AmbiguityCollaboration

Industry Keywords

LLMsRAG SystemsAI-Powered Applications

About the role

Key responsibilities & impact

Build end-to-end product features across frontend, backend, and AI integrations.
Design agent workflows that handle planning, tool use, failure, and recovery across multiple steps.
Integrate LLMs, memory, and external tools into systems that behave reliably under real-world conditions.
Design real-time AI interactions with streaming, partial results, and tight latency constraints.
Improve system reliability, observability, and fallback mechanisms.
Collaborate closely with ML, backend, and product teams to ship features end-to-end.
Continuously iterate based on real usage and failure modes.

Requirements

What you’ll need

Strong experience in Full Stack Engineering (Frontend and Backend).
Artificial Intelligence (AI) experience required.
Solid understanding of system design and API architecture.
Experience working with LLMs, RAG systems, or AI-powered applications.
Ability to handle ambiguity and make pragmatic engineering decisions.
Strong ownership; able to take features from idea to production.
Comfort working in fast-moving environments with evolving requirements.

Benefits

Comp & perks

medical insurance
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