AI Analyst Fulltime Indianapolis, IN (Onsite)

Role: AI Analyst

Location: Indianapolis, IN (Onsite)

Fulltime - Permanent

Salary: $95,000 -$105,000 year





Job Description

Must 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.