AI Analyst || Fulltime || Indianapolis, IN (Onsite)

Role: AI AnalystLocation: Indianapolis, IN (Onsite)Fulltime - Permanent Salary: $95,000 -$105,000 year Job DescriptionMust Have Technical/Functional Skills • 2-4 years of experience in a technical analyst, AI support, or systems configuration role. • Hands-on experience working with LLMs (e.g., OpenAI, Anthropic Claude, AWS Bedrock) -configuration, API usage, and prompt engineering. • Proficiency in Python for scripting, log parsing, and light automation. • Practical AWS knowledge: navigating CloudWatch logs, Lambda, S3, and IAM to support troubleshooting. • Strong analytical and problem-solving skills with attention to detail. • Required Technologies: Gen-AI, AI Agent engineering, MLOps, MCP,Python, Angular/React/VueJs, NODEJS, AWS platform Roles & Responsibilities • Design and build end-to-end AI-powered applications to enhance Clinical Operations platforms. • Develop and deploy AI capabilities (LLM applications, RAG pipelines, agent orchestration) to support clinical, regulatory, and business workflows. • Integrate AI solutions into enterprise environments ensuring scalability, security, and compliance. • Architect and implement integrations with various platforms and enterprise data ecosystems using API-first and microservices-based approaches. • Design and optimize data models, pipelines, and transformations to ensure high-quality, reliable, and governed datasets. • Ensure alignment with enterprise data standards, metadata management, and traceability requirements. • Embed Responsible AI principles, ensuring fairness, transparency, explainability, and regulatory compliance • (e.g., GxP, data privacy). • Establish governance, auditability, and validation processes aligned with clinical standards. • Develop production-grade code, perform code reviews, and ensure engineering best practices. • Monitor and optimize system performance, scalability, and reliability across applications and pipelines. • Identify opportunities to improve system reliability, response quality, and cost efficiency. • Troubleshoot complex issues across data, infrastructure, and AI layers. • Leverage cloud platforms (AWS/Azure) and modern DevOps/MLOps practices to enable secure, scalable deployments. • Lead end-to-end delivery—from ideation and prototyping to full-scale production rollout. • Partner with stakeholders to convert concepts into production-ready solutions delivering measurable business value. • Collaborate with cross-functional teams to identify high-impact opportunities aligned with business priorities. • Provide technical leadership, guiding architecture decisions, best practices, and problem resolution. • Troubleshoot production issues by reviewing AWS logs (CloudWatch, Lambda, S3) and coordinating resolution.