Sr AI Solutions Developer

Senior AI Solutions DeveloperRole DescriptionThis is a full-time on-site role for a Senior AI Solutions Developer at Cogitate based in Marietta, GA. The Senior AI Solutions Developer will be responsible for:Lead the design and implementation of AI agents capable of reasoning, planning, and executing tasks autonomously or semi-autonomously.Architect, build, and maintain scalable AI workflows that orchestrate tasks across models, APIs, and business logic layers.Integrate LLMs (e.g., OpenAI, Anthropic, Azure OpenAI) into structured agent workflows using frameworks like LangChain, Semantic Kernel, or custom solutions.Design and optimize retrieval-augmented generation (RAG) pipelines and other hybrid AI architectures for production-scale performance, accuracy, and cost efficiency.Define technical standards and best practices for AI development, including evaluation frameworks, guardrails, and responsible AI practices.Mentor junior and mid-level engineers through code reviews, design reviews, and pair programming.Collaborate with product teams and stakeholders to translate business use cases into AI-powered features, and influence the AI product roadmap.Evaluate emerging AI technologies, models, and frameworks and make build-vs-buy recommendations.Own production reliability of AI systems, including monitoring, observability, latency/cost optimization, and incident response.QualificationsBachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. 4-7 years of software engineering experience, including 3+ years working with LLMs, ML systems, or AI-powered applications.Expert proficiency in Python and relevant AI/ML libraries.Deep experience with LLMs, prompt engineering, fine-tuning, and API integration with foundation models.Proven experience designing and shipping production AI agent systems using frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, or custom solutions.Experience building or integrating workflows using tools like Airflow, Prefect, or custom orchestrators.Hands-on experience with vector databases (e.g., Pinecone, Weaviate, pgvector) and embedding-based search.Experience with LLM evaluation, testing, and observability tooling (e.g., LangSmith, Weights & Biases, custom eval harnesses).Strong understanding of RESTful APIs, cloud platforms (Azure, AWS, or GCP), and containerized deployments (Docker, Kubernetes).Experience designing secure, compliant AI solutions, including data privacy, access control, and guardrails against prompt injection and model misuse.Solid grasp of software engineering best practices, including version control (Git), CI/CD, testing, and code reviews.Demonstrated technical leadership: mentoring engineers, driving architectural decisions, and leading cross-functional initiatives.Excellent communication skills, with the ability to explain AI concepts and trade-offs to technical and non-technical stakeholders.PreferredExperience in the insurance or financial services domain.Experience with MLOps practices and model lifecycle management.Experience with the traditional ML and Data Science Domain