Agentic AI Engineer

Job summary

Design, build, integrate, and optimize agentic AI systems and autonomous workflows, including AI agents, neural network models, and NLP solutions. Collaborate with cross-functional teams to translate business needs into scalable, reliable, and secure production systems, while evaluating tools, optimizing performance, and documenting implementation practices.

Job details

Company Description Accion Labs is an AI-first, platform-led innovation engineering company headquartered in Pittsburgh, focused on transforming businesses through next-generation technologies. With a global footprint across 23 locations and a team of over 5,000 professionals, including more than 1,000 trained in AI and Generative AI, the company helps organizations modernize and scale through engineering excellence, proprietary IP, and robust delivery models. Core services span digital engineering, cloud and platform engineering, data and AI solutions, enterprise system automation, and agentic AI solutions. Accion Labs has delivered 50+ GenAI implementations and built 34+ proprietary platforms, enabling clients to launch AI-powered products and optimize operations across industries. The company is recognized by leading analyst firms and business publications for its innovation, rapid growth, and strength in software product engineering and AI services. Role Description The Agentic AI Engineer role is a remote, contract position focused on designing, building, and optimizing agentic AI systems that solve complex business problems. Day-to-day responsibilities include developing and integrating AI agents using modern machine learning frameworks, implementing pattern recognition and neural network models, and working with NLP techniques to build intelligent, autonomous workflows. The role involves collaborating with cross-functional teams to translate business requirements into technical architectures, contributing to software development and integration of AI components into existing platforms, and ensuring scalability, reliability, and security of deployed solutions. The Agentic AI Engineer will also evaluate emerging AI tools, run experiments, optimize model performance, and contribute to best practices and documentation for agentic AI implementations. Qualifications Strong foundation in Computer Science and Software Development, including data structures, algorithms, APIs, and distributed systems. Experience with Neural Networks and Pattern Recognition for building and optimizing machine learning and deep learning models. Hands-on expertise in Natural Language Processing (NLP), including working with LLMs, text processing, and conversational AI. Proficiency with modern AI/ML frameworks and tools (e.g., PyTorch, TensorFlow, LangChain, vector databases, orchestration frameworks for AI agents). Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related technical field, or equivalent practical experience. Experience designing and deploying production-grade AI systems in cloud environments (AWS, Azure, GCP) with CI/CD and MLOps practices. Strong problem-solving skills, ability to work independently in a remote setting, and comfort collaborating with global, cross-functional teams. Background in agentic AI architectures, multi-agent systems, or autonomous workflows is a strong plus. Experience in enterprise or platform engineering environments and familiarity with security,

What you’ll do

Design, build, integrate, and optimize agentic AI systems and autonomous workflows, including AI agents, neural network models, and NLP solutions. Collaborate with cross-functional teams to translate business needs into scalable, reliable, and secure production systems, while evaluating tools, optimizing performance, and documenting implementation practices.

Requirements

Requires a strong foundation in computer science and software development, hands-on experience with neural networks, pattern recognition, NLP, and modern AI/ML frameworks, plus a relevant bachelor's or master's degree or equivalent experience. Candidates should have experience deploying production AI systems in cloud environments with CI/CD and MLOps practices, and be able to work independently and collaborate remotely; agentic AI or multi-agent experience is a plus.

Listed skills

• CI/CD · Preferred
• Machine learning · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Agentic AI
• Machine Learning
• Deep Learning
• Neural Networks
• Pattern Recognition
• Natural Language Processing
• Large Language Models
• PyTorch
• TensorFlow
• LangChain
• Vector Databases
• Multi-Agent Systems
• Cloud Computing
• MLOps
• CI/CD
• Distributed Systems

Job areas

• Technology
• Software
• Data & Analytics
• Engineering

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