Lead AI Engineer – Agentic Engineering

🔥 0 minutes ago

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Blend360

WebsiteLinkedInAll Job Openings

501 - 1000 employees

🏥 Healthcare

🏨 Hospitality

✈️ Travel

💰 $100M Private Equity Round on 2022-08

Healthcare • Hospitality • Travel

Blend360 is a professional services company specializing in AI, data analytics, and data-driven solutions. They work with Fortune 1000 and large enterprise brands to tackle significant challenges by integrating people and artificial intelligence. Blend360 focuses on several domains including business intelligence, data engineering, data science, MLOps, and data governance. Their industries of expertise encompass financial services, energy, healthcare and life sciences, retail, technology, media & telecom, and travel & hospitality. Blend360 is recognized for their AI and data solutions, having earned accolades such as "AI-Enabling Solution of the Year" and being listed among the "Top Generative AI Service Providers 2024.

📋 Description

• Drive adoption of Agentic Engineering practices across the software development lifecycle using AI agents to augment and automate engineering workflows • Leverage Claude Code, Claude Code Skills, PI, Hermes Agent, and comparable AI coding/engineering agents in day-to-day software development • Build AI-assisted workflows for requirements analysis, code generation, code understanding, refactoring, testing, debugging, documentation, code review, and deployment • Design agent workflows that understand large codebases, manage context, use tools, execute multi-step engineering tasks, and recover from failures • Establish practices for context management, context engineering, tool calling, agent orchestration, guardrails, human-in-the-loop workflows, and autonomous task execution • Design and implement evaluations measuring agent correctness, reliability, code quality, task completion, regression, and effectiveness • Evaluate emerging agentic coding tools and techniques to improve engineering productivity and software quality • Architect and develop production-grade multi-agent and agentic systems for complex, multi-step tasks • Design agent architectures covering planning, reasoning, tool use, memory/context, execution, reflection, validation, and error recovery • Integrate agents with APIs, databases, enterprise systems, developer tools, and external services • Develop reliable tool-use and MCP-based integrations where appropriate • Build production-grade LLM applications using LangGraph, LangChain, or equivalent orchestration frameworks • Implement RAG, semantic search, vector retrieval, structured outputs, and other LLM application patterns • Establish observability, evaluation, monitoring, security, and guardrails for agentic applications • Provide technical leadership across AI-powered software products and platforms • Apply software engineering principles including system design, modular architecture, API design, scalability, reliability, testing, CI/CD, and maintainability • Build production-quality services and APIs using Python, FastAPI, Docker, Kubernetes, and cloud platforms • Collaborate with engineering, product, data, and client teams to translate business problems into scalable technical solutions • Conduct technical design reviews and mentor AI/software engineers • Establish engineering standards and best practices for AI and agentic applications • Lead Agentic AI initiatives and influence architecture and engineering decisions across teams • Prototype emerging technologies and transition successful approaches into reliable production solutions • Collaborate with clients and internal stakeholders to identify opportunities for measurable Agentic AI value

🎯 Requirements

• 6+ years of software engineering / AI engineering experience • Strong hands-on development experience and software engineering fundamentals • Experience building production-grade applications and services • Demonstrable experience building production-grade Agentic AI systems beyond simple chatbots or basic RAG applications • Strong understanding of Agentic Evaluation / Agent Evals • Experience creating evaluation datasets, test scenarios, metrics, automated regression tests, and quality gates • Ability to evaluate planning, tool use, reasoning trajectory, context handling, reliability, safety, latency, cost, and task completion • Strong hands-on experience with Python and modern backend/API development • Experience with LLMs, GenAI, agent orchestration, tool calling, and RAG • Experience with agent frameworks such as LangGraph, LangChain, CrewAI, AutoGen, Google ADK, or equivalent • Strong understanding of multi-agent architectures, planning, reasoning, context management, tool use, memory, and agent execution • Experience with evaluation frameworks to measure and improve AI/agent performance • Experience with cloud, containers, CI/CD, APIs, databases, and production deployments • Strong understanding of software architecture, debugging, testing, scalability, and production engineering practices • Practical exposure to using AI agents as engineering tools within the SDLC • Experience with Claude Code / Claude Code Skills, PI, Hermes Agent, or comparable agentic development platforms is highly valuable • Experience with MCP and building MCP servers/tools is nice to have • Experience with Claude, GPT, Gemini, Llama, or other frontier models is nice to have • Experience with AWS, Azure, or GCP is nice to have • Experience with Kubernetes, Docker, CI/CD, and cloud-native architectures is nice to have • Experience with LLM observability and tracing is nice to have • Experience with Langfuse, Arize Phoenix, OpenTelemetry, or similar is nice to have • Experience implementing automated agent evaluations, regression testing, and quality gates is nice to have • Experience with distributed systems and scalable AI inference is nice to have • Experience in consulting/client-facing environments is nice to have