Satya Achanta

Sr Software Engineer

Ithaka | Ann Arbor, MI | Nov 2019 - Present

• Act as a lead-minded engineer across admin portals, reporting workflows, and public APIs, owning ambiguous initiatives end to end.
• Led modernization by decomposing legacy services into AWS Lambda and Step Functions workflows, improving scalability and reducing operational overhead.
• Improved release velocity by 3x through AI-assisted development workflows that accelerated implementation, debugging, testing, and developer self-sufficiency.
• Applied AI-enabled engineering practices with Codex and Copilot for code scaffolding, refactoring, testing, and full-stack feature implementation.
• Created skills and instructions that helped AI tools understand repo conventions, generate tests in the team's style, and support onboarding.
• Encouraged responsible adoption of AI-assisted workflows and helped shape expectations for reviewing AI-generated code effectively.
• Drove engineering standards through clearer repo patterns, stronger testing practices, improved linting, and more consistent frontend architecture decisions.
• Partnered with product owners and stakeholders to shape technical roadmaps, identify delivery risks, and reduce execution bottlenecks.
• Designed and maintained CI/CD pipelines with GitHub Actions, GitLab, Jenkins, Docker, and Kubernetes.
• Introduced a real-time feedback mechanism that reduced the customer feedback loop by 50%.
• Mentored junior and mid-level engineers through debugging support, design reviews, onboarding, and day-to-day technical guidance.

Software Engineer

Infor | Ann Arbor, MI | May 2015 - Nov 2019

• Built and maintained enterprise-grade applications for automotive clients using Angular and Java/Spring.
• Partnered with the Principal Architect to review designs, evaluate tradeoffs, and improve long-term maintainability across modules.
• Led frontend modernization across legacy Angular codebases, introducing linting and coding standards that improved consistency and reduced defects.
• Optimized data access layers using Hibernate and SQL to improve reporting performance and reliability.
• Contributed to Agile delivery and CI practices through automated testing and Jenkins pipelines.

Product Builder

Conceived, architected, and delivered a production-grade fantasy sports and MichCA platform experience, owning the product lifecycle from ideation and UX design through deployment and ongoing optimization.

• Designed a serverless full-stack architecture with Next.js, Prisma, and Neon Postgres, reducing match-result computation from 30 minutes to 15 seconds.
• Built core product capabilities including admin workflows, leaderboards, database design, Excel ingestion flows, and a mobile-responsive application experience.
• Developed admin workflows for managing users, teams, and weekly operations, reducing operational effort for league administration.
• Designed data models for historical fantasy picks by user/week, leaderboard and scoring history, and team/user relationships to support downstream analytics and AI-based analysis.
• Built a production-ready AI analysis feature using the OpenAI API to evaluate users' historical picks and generate strengths, weaknesses, recommendations, and relative standings.
• Aggregated structured historical data from the database and sent it to the OpenAI API for LLM-generated analysis over structured inputs.
• Continuously monitored performance, iterated on APIs and data models, and optimized the platform for sustainable growth and low operational overhead.

Prototype / Learning Project

Built a RAG-style conversational resume agent in Python to deepen hands-on understanding of retrieval-based AI workflows.

• Chunked resume content, stored embeddings in vectorized form, and implemented a conversational retrieval agent in Python.
• Used LangChain text splitters in the ingestion pipeline and built a user-input-driven conversation flow grounded in indexed resume content.
• Practiced retrieval design patterns that can support future portfolio Q&A experiences without overclaiming production readiness.

Full-Stack Product Builder

Built a focused marketplace for cricketers to buy and sell used gear locally, making it easier for players to recover value from unused equipment and for other players to find affordable gear quickly.

• Improved discoverability with search across titles, descriptions, cities, and tags so buyers can find relevant bats, pads, helmets, and other gear without digging through generic social posts or chat threads.
• Made listing creation practical for everyday users with structured forms, multi-image uploads, cover-photo selection, price and condition fields, and direct seller contact details after sign-in.
• Added account tools for sellers to manage their own listings, edit details, mark items as sold, and stay within simple listing limits, keeping the marketplace current instead of filling with stale posts.
• Introduced an approval workflow with admin moderation, rejection reasons, and hidden-until-approved publishing so the marketplace can build trust and stay usable as activity grows.
• Modeled the product around community reuse and accessibility, helping newer players access lower-cost equipment while giving existing players a cleaner path to circulate gear back into the cricket ecosystem.