As a Software Engineer (AI Systems & Agentic Platforms), you will design and build next-generation intelligent systems that blend software, models, and automation into cohesive, adaptive platforms. Your mission is to create deployable, self-improving systems—software that can reason, generate, evaluate, and iteratively improve its own outputs. You will focus on building agent-driven systems, evaluation frameworks, and protocol-based integrations (MCP) that enable seamless interaction between models, tools, and real-world workflows. About the team Our team operates at the intersection of software engineering, AI systems, and rapid experimentation. We build platforms that enable intelligent automation at scale—ranging from agent orchestration to developer-facing AI systems. We emphasize iteration speed, practical impact, and systems that learn from usage, not just static training. The work often involves ambiguous problem spaces where we define patterns as we build them. What you'll do Design and build end-to-end agentic systems capable of multi-step reasoning, planning, and tool execution. Develop AI-assisted development workflows that accelerate how software is written, tested, and iterated. Build agent evaluation frameworks (offline + online) to measure quality, reliability, and system behavior. Implement feedback-driven systems that continuously improve outputs using real-world signals. Architect and integrate MCP-based systems to standardize interactions between models, tools, and services. Develop multi-agent workflows with coordination, delegation, and dynamic task execution. Build scalable services (APIs, pipelines, event-driven systems) supporting real-time and batch use cases. Introduce patterns for observability, debugging, and traceability in AI-driven systems. Rapidly prototype and iterate on new system behaviors, workflows, and interaction models. Contribute to shaping engineering practices for AI-native application development. What you'll bring Experience building production systems that integrate AI/ML components into real-world applications. Familiarity with LLM-based systems, agent workflows, or tool-augmented models. Hands-on work with evaluation, feedback loops, or iterative system improvement. Ability to design and ship end-to-end solutions quickly, balancing experimentation with reliability. Comfort working in open-ended problem spaces with evolving requirements. Proficiency in Python and modern backend development, with an emphasis on building usable systems. Experience integrating external tools, APIs, or structured data into intelligent workflows. Strong ownership mindset with a focus on shipping, learning, and improving systems continuously. Bonus / Signals we value Experience building AI-powered developer tools or automation systems. Work on agent frameworks, orchestration layers, or evaluation harnesses. Familiarity with protocol-driven systems (e.g., MCP or similar abstractions). Interest in human-AI interaction, rapid prototyping, or unconventional system design. Track record of building things quickly and iterating based on real feedback.
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Job Type
Full-time
Career Level
Mid Level
Number of Employees
1-10 employees