Senior Engineer

Job Title : Senior GenAI Engineer (Senior Agentic Engineer)

Location: Bangalore

About Us

Asper.ai is a cutting-edge AI-based SaaS company focused on revolutionizing enterprise decision making, through demand planning and Revenue growth management for the Consumer-Packaged Goods (CPG) industry.

Role Summary

We are looking for an Agentic Engineer above with 7–10 years of overall experience, including a strong software engineering background and recent hands-on experience in GenAI / Agentic Engineering. The role requires someone who has owned and scaled entire product engineering systems and can design, build, and deploy enterprise grade autonomous and semiautonomous AI agents that power high impact decision workflows.

You will work on planning–execution–verification loops, tool using agents, multiagent coordination, latency optimization, embeddings, context management, and observability—integrated tightly with large datasets, enterprise data, applications, and security controls.

Key Responsibilities

• Design and implement agentic workflows (single agent and multiagent) for complex business decisions and task automation.
• Build agents that plan, reason, act, verify, and recover using tools, memory, and context graphs
• Integrate LLMs (e.g., GPT4 / GPT4o or equivalent) with enterprise systems via APIs and event driven architectures.
• Own and scale end-to-end product engineering, from architecture and backend systems to deployment, observability, and production reliability.
• Develop orchestration using frameworks such as LangChain, Semantic Kernel, or custom agent runtimes.
• Implement guardrails: error handling, retries, fallback logic, deterministic shells around probabilistic cores.
• Instrument observability and evaluation (task success, reliability, latency, safety) for agent performance.
• Collaborate with product, domain SMEs, and data teams to translate business logic into executable agent behaviours.
• Ensure security, access control, compliance, and auditability across agent actions and decisions.

Requirements

• 7–10 years of overall experience, with strong software engineering foundations and the last 2 years in GenAI / Agentic Engineering.
• Strong experience building LLM based or agentic systems (tool use, memory, routing, planning).
• Strong expertise in Python + LLMs or C++ + LLMs, with modern backend and production engineering practices.
• Hands-on expertise in prompt engineering, latency optimization, embeddings, context management, reasoning patterns, and large datasets.
• Experience with orchestration and evaluation frameworks (e.g., LangChain agents, LangSmith, TruLens, RAGAS).
• Experience owning and scaling entire product engineering charters, including architecture, engineering execution, productionization, and scale-up.
• API integration and data transformation across enterprise systems.
• Production mindset: logging, monitoring, reliability, and failure handling.

Good to Have

• Experience with multiagent architectures (agent to agent communication, control planes).
• Familiarity with Azure AI stack / cloud native deployments.
• Experience in regulated or high-stake domains (finance, healthcare, pricing, RGM, etc.).
• Exposure to optimization or finetuning approaches (LoRA, QLoRA, evaldriven iteration).
• Preferred candidates from large MNCs with large-scale data and LLM experience, or from small/mid-sized organizations with demonstrably strong LLM expertise.

Education

• Bachelor's degree in computer science, Information Technology, or a related field is a must.

Experience

• 7–10 years of overall experience, including the last 2 years in GenAI / Agentic Engineering, with hands-on experience building LLM-based or agentic systems and owning/scaling production-grade product engineering.