AI Engineer

12 Month Contract-To-Hire : W2Fully Remote NOT looking for a Data Science background - looking for Software focus! Required Qualifications: • Bachelor's or Master's degree in Computer Science, Engineering, or related field. • 5+ years of experience in AI engineering, backend development, or full-stack development. • Strong proficiency in Java (mandatory) for backend development, with hands-on experience using Spring Boot. • Strong proficiency in Python for AI/ML development and orchestration. • Proficiency in JavaScript/TypeScript and modern frontend frameworks (Angular/React). • Hands-on experience with LangChain, ADK, and agent orchestration frameworks. • Experience with LLMs (OpenAI, Azure OpenAI, Hugging Face) and prompt engineering. • Hands-on experience with GCP and Azure services for AI/ML workloads and application deployment. • Experience with FastAPI/Django, Spring Boot, and ML libraries (TensorFlow, PyTorch, scikit-learn). • Familiarity with vector databases (Pinecone, Weaviate, FAISS). • Experience with containerization (Docker, Kubernetes) and CI/CD pipelines. • Strong understanding of ML algorithms, deep learning, and enterprise system integration. • Excellent communication skills and ability to work in Agile environments. Job DescriptionYou will be responsible for designing, developing, and deploying robust and scalable AI-native applications that leverage artificial intelligence (AI) and machine learning (ML) services and tools. You bring expertise in full-stack web application development and backend service development using Java (Spring Boot) and Python, along with modern JavaScript frameworks such as Angular and React. You have a strong foundation in machine learning principles, natural language processing (NLP), and Generative AI, with hands-on experience delivering solutions across Google Cloud Platform (GCP) and Microsoft Azure through the full application lifecycle (development, deployment, telemetry, logging, and monitoring). Responsibilities:• Design, develop, and maintain AI‑native web applications, APIs, and backend services, including Retrieval‑Augmented Generation (RAG) solutions.• Develop Java‑based backend services and microservices (Spring Boot) to support AI workflows, orchestration, and enterprise integrations.• Utilize Google Cloud Platform (GCP) services (e.g., Vertex AI, BigQuery, Cloud Storage) to build, fine‑tune, and deploy AI‑native applications.• Utilize Microsoft Azure services (e.g., Azure Machine Learning, Azure OpenAI Service, Azure Synapse Analytics / Azure Data Explorer, Azure Blob Storage) to build, train, and deploy AI‑native applications.• Implement and integrate AI/ML models and ML services into applications using Python and Java, exposing capabilities through RESTful APIs.• Collaborate with data scientists, product managers, architects, and automation teams to translate business requirements into scalable technical solutions.• Fine‑tune and evaluate models for use‑case‑specific needs across cloud platforms.• Implement prompt engineering, agent workflows, and RAG pipelines using LangChain, LangGraph, ADK, and related orchestration frameworks.• Develop modular, scalable architectures for AI‑powered web applications and APIs.• Integrate LLMs with enterprise systems, databases, and external services.• Implement vector databases for semantic search and build connectors for structured and unstructured data ingestion.• Follow Agile/Scrum practices and document technical designs, workflows, and best practices. Work closely with automation teams, architects, and product owners to deliver end-to-end AI solutions.• Document workflows and best practices for AI integration. Compensation:$70/hr - $75/hr Exact compensation may vary based on several factors, including skills, experience, and education. Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.