Tech Lead for AI Agents (Production-Grade Development)
Job Description
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We’re looking for a hands-on Tech Lead to build production-grade AI agents and lead delivery from architecture to deployment. You’ll code, make technical decisions, and help the team ship reliable AI-powered products quickly.
Responsibilities:
- Build agent systems with Hermes Agent, OpenClaw, Letta, Agent Zero, OpenHands, or similar open-source runtimes.
- Use frameworks such as OpenAI Agents SDK, LangGraph, Google ADK, Vercel AI SDK, CrewAI, AutoGen, or Mastra.
- Develop reusable skills, tools, subagents, workflows, persistent memory, scheduled tasks, and messaging integrations.
- Integrate OpenAI, Anthropic, Gemini, open-weight, and local models through tool calling, structured outputs, streaming, and model routing.
- Connect agents to systems using MCP, A2A, REST APIs, webhooks, browsers, terminals, and computer-use tools.
- Build RAG and context systems using pgvector, Pinecone, Weaviate, Elasticsearch, or equivalent technologies.
- Establish evaluations and observability with LangSmith, Braintrust, Phoenix, OpenTelemetry, or provider tracing.
- Secure autonomous agents using sandboxing, least-privilege access, approval gates, secrets management, audit trails, and prompt-injection defenses.
- Use Codex, Claude Code, Cursor, or GitHub Copilot to accelerate delivery.
- Own technical plans, production quality, latency, reliability, and model costs.
Requirements
- Strong software engineering and hands-on technical leadership experience.
- Experience shipping AI agents or LLM applications into production.
- Strong Python or TypeScript skills and cloud infrastructure experience.
- Practical knowledge of agent orchestration, memory, tool use, RAG, evaluations, and human-in-the-loop design.
- Familiarity with current trends such as self-improving agents, reusable agent skills, local-first and bring-your-own-model runtimes, multimodal and computer-use agents, MCP/A2A interoperability, durable execution, and eval-driven development.
Benefits
- Remote work (Vietnam-based)
- Full-time: 8 hours per day, aligned with Portugal business hours (WET/WEST)
- Freelance / Service Agreement
- Hourly Rate: $20-$25
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View Company ProfileAlongside is an innovative, enterprise-grade digital mental health and student wellness platform engineered to operate as the definitive, school-integrated support infrastructure layer for modern K-12 education systems. Operating as a mission-critical clinical-intelligence engine, the platform eliminates the severe operational friction of traditional, overburdened school counseling systems—which frequently suffer from extreme student-to-counselor ratios, delayed crisis intervention, and fragmented mental health tracking—by seamlessly deploying an advanced, AI-driven tiers of care support assistant. Moving far beyond traditional, legacy clinic models or unmonitored wellness widgets, Alongside empowers public school districts, charter networks, and educational institutions to dynamically synchronize their tier-1 mental health interventions, real-time student sentiment telemetry, and immediate counselor escalations with elite, scalable, and audit-ready precision. Under the hood, their sophisticated proprietary validation infrastructure—built in deep collaboration with adolescent clinical psychologists, bolstered by strict COPPA and FERPA privacy compliance protocols, and persistent safety-keyword monitors—natively manages high-concurrency student interactions, automated self-regulation exercises, and urgent risk reporting. What sets Alongside apart is its uncompromising dedication to safe, frictionless student orchestration; by bridging the gap between performance-intensive, high-stakes clinical safety frameworks and accessible, highly engaging gamified chat interfaces, the platform enables modern educational organizations to radically accelerate their care-delivery velocity, eliminate systemic counseling bottlenecks, and build an unassailable foundation for continuous student well-being and academic thriving in the modern, technology-transformed landscape.
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