Software / Platform Engineer II

Job Responsibilities · Architect and deliver AI-driven solutions that address high ‑ value business needs, including document interpretation, automated decision flows, feedback generation, dashboard creation, data reconciliation, and approval management. · Lead the development of agent-based workflows using LLMs, retrieval pipelines, and multi ‑ agent orchestration frameworks. · Build Composite AI architectures, combining language models, search, business rules, embeddings, and analytics. · Proven experience designing, developing, and deploying Generative AI (GenAI) solutions using large language models (LLMs) such as GPT, Llama, Claude, etc · Design and optimize context pipelines—chunking strategies, prompting structure, memory systems, and vector retrieval mechanisms. · Develop robust backend components and API integrations supporting AI agents, Azure AI services, and MCP-based tools. · Experience with modern GenAI frameworks and libraries (e.g., LangChain, LlamaIndex, Hugging Face Transformers). · Evaluate new use cases, propose viable AI solutions, and guide stakeholders through feasibility and solution design. · Ensure solutions align with responsible AI standards, quality benchmarks, and enterprise governance requirements. · Collaborate with architects, product managers, and business teams to align AI initiatives with enterprise goals. · Monitor system performance, optimize agent behaviors, and evolve solutions post-deployment. · Extensive experience with Microsoft Azure services and cloud architecture patterns · Deep understanding of CI/CD pipelines, automated testing, and DevOps practices · Experience with microservices architecture, API design, and distributed systems · Experience mentoring engineers and building high-performing teams . Knowledge, Skills and Abilities Education · Bachelor’s degree or master’s in computer science, Engineering, or related technical discipline. Experience · 3–5+ years of AI engineering experience, ideally within large organizations or enterprise platforms. · Proven track record of leading AI or GenAI initiatives, from concept to deployment. Knowledge and skills (general and technical) Strong command of: · Large Language Models and modern GenAI techniques · Agentic design principles (tool ‑ augmented agents, planners, multi-agent coordination) · Retrieval-based systems (embeddings, vector search, context assembly) · Proficiency in Python and experience developing scalable backend components and APIs. · Hands-on expertise with Azure AI / Azure OpenAI, Azure Functions, APIM, storage, and related cloud services. · Experience building solutions that go beyond simple automation tools—focusing instead on intelligent, adaptive systems. · Ability to collaborate directly with business partners, understand real workflows, and translate them into AI-powered solutions. Other Requirements (licenses, certifications, specialized training – if required) Experience with advanced Agentic frameworks: · LangChain, LangGraph, Azure AI Agents · Multi-agent routing, tool-calling patterns, DAG-based orchestration · Hands-on experience with vector databases (Azure AI Search, Pinecone, FAISS). · Exposure to MCP (Model Context Protocol) and enterprise tool-chains integrating LLM agents with backend systems. · Prior involvement in building solutions for domains such as: · Operational decision flows · Document-heavy processes · KPI/insights generation · Approval or workflow automation · Familiarity with cloud-native architecture, DevOps pipelines, and observability tooling. · Experience with AI developer tools: GitHub Copilot, OpenAI’s code assistants, or similar systems. · Understanding of enterprise data protection, compliance considerations, and responsible AI practices.