Applied AI Engineer

Zycus is looking for a high-intelligence, high-throughput engineer who has shipped enterprise agents (autonomous / workflow / conversational) to solve real domain problems.

All successful candidates are expected to dive deep into problem areas of Zycusʼ interest and invent technology solutions to not only advance the current products, but also to generate new product options that can strategically advantage the organization.

Roles and Responsibilities

Person has to be hands-on and an individual contributor with leadership impact

• Design and implement agentic architectures: single- and multi-agent, hierarchical flows, and tool-rich execution.
• Build production agents for domain workflows (retrieval, reasoning, tool use, approvals, human-in-the-loop).
• Own context engineering: structuring prompts, memory, retrieval, grounding, and evaluation loops.
• Make agents scale, concurrency, state & persistence, streaming, evaluation/telemetry, and cost controls.
• Partner with product/domain teams to convert ambiguous problems into shipped agents with measurable outcomes.

• 6–15 years of hands-on experience in software engineering, with at least 3 years in applied AI, LLMs, or agentic system design.
• Proven experience in building and deploying enterprise AI applications — ideally workflow, conversational, or decision agents.
• Strong proficiency in Python, LangChain, LlamaIndex, or similar frameworks for agentic orchestration.
• Deep understanding of LLMs, embeddings, retrieval-augmented generation (RAG), and multi-agent systems.
• Solid experience with cloud platforms (AWS, Azure, GCP) and MLOps tools for scalable AI deployment.
• Strong grasp of data engineering concepts, including vector stores (Pinecone, FAISS), document indexing, and contextual retrieval.
• Ability to lead through influence — guiding technical decisions, mentoring peers, and driving innovation across teams.

Must Have

• 6+ years total software engineering; strong fundamentals in Java or Python or JS/TS (any stack: Java stack, MEAN, or Python).
• Demonstrated track record of building and deploying agents (workflow/autonomous/chat) with tools & external systems.
• Comfort with agent frameworks/patterns (e.g., graph/workflow agents, crew-style collaboration), tooling protocols, and RAG-plus grounding.
• Deep prompt/context engineering skills; knows when to use structure, when to retrieve, and how to evaluate.

Why You Should Join Zycus

• Work on cutting-edge applications powered by AI-assisted development workflows.
• Collaborate with a forward-thinking engineering team that values innovation and continuous learning.
• Access to premium AI development tools to boost productivity and code quality.
• Competitive compensation, flexible work arrangements, and opportunities for career advancement.