Senior AI Developer

About the job

Job Title: Senior AI Developer Location: Work from Office Reports To: CPTO Experience Required: 6–8 years (with 3+ years in advanced AI/LLM/RAG systems) Role Overview We are seeking a highly experienced Senior AI Developer with deep expertise in Agentic AI systems to design, build, and scale autonomous AI agents capable of reasoning, planning, tool usage, multi-step execution, and real-world decision-making. This role is not limited to prompt engineering. We are looking for someone who has built production-grade, multi-agent systems that integrate LLMs, vector databases, APIs, orchestration layers, and observability frameworks. You will play a critical role in transforming our platform into an AI-First architecture by embedding intelligent agents across workflows, automation systems, and customer-facing applications. Key Responsibilities 🧠 Agentic AI Architecture • Design and implement autonomous AI agents capable of: • Multi-step reasoning and task decomposition • Tool usage (APIs, databases, search, calculators, external systems) • Memory management (short-term + long-term) • Self-reflection and corrective loops • Architect multi-agent collaboration systems (Planner → Executor → Critic models) • Implement ReAct, Tree-of-Thought, or other reasoning frameworks ⚙️ System Engineering & Integration • Integrate LLMs (OpenAI, Anthropic, open-source models) into scalable backend systems • Build RAG pipelines using vector databases (Pinecone, Weaviate, OpenSearch, FAISS, etc.) • Develop tool invocation frameworks and function-calling pipelines • Optimize token usage, latency, and cost at scale • Implement streaming architectures for real-time AI responses 📊 Production-Grade Engineering • Deploy AI systems on Kubernetes / cloud infrastructure (AWS / Azure / GCP) • Build observability for: • Prompt performance • Hallucination tracking • Agent failure modes • Token cost monitoring • Implement guardrails, safety layers, and compliance filters • Design fallback and retry strategies 🔬 Advanced Capabilities (Preferred) • Fine-tuning or LoRA adaptation of LLMs • Building evaluation frameworks (LLM eval pipelines, scoring agents) • Reinforcement Learning from Human Feedback (RLHF) familiarity • Multi-modal AI (vision + text) • AutoGPT / LangGraph / CrewAI / Semantic Kernel experience What We’re Looking For • Someone who has built real production AI agents, not just demos • Ability to think architecturally (cost, scale, latency, security) • Deep understanding of LLM limitations and mitigation strategies • Strong debugging ability in complex reasoning chains • Passion for building autonomous systems that replace manual workflows Nice to Have • Experience building AI copilots • Experience in ecommerce / fintech / automation platforms • Research background in multi-agent systems • Published papers or open-source contributions • Experience handling 1M+ AI requests/day systems Impact of This Role You Will • Architect AI agents that automate complex workflows • Build multi-agent AI systems that drive productivity gains • Reduce operational cost through intelligent automation • Lay the foundation for an AI-First enterprise platform KPIs for Success • % automation achieved through AI agents • Reduction in manual intervention • AI response latency under defined SLA • Token cost efficiency improvement • Agent accuracy and task completion rate

Requirements

• Python
• Agentic AI
• LLMs
• RAG architecture
• Kubernetes
• AWS
• Azure
• GCP

Preferred Technologies

• Python
• Agentic AI
• LLMs
• RAG architecture
• Kubernetes
• AWS
• Azure
• GCP