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Shashank Tiwari

AI Engineer

AI Engineer specializing in RL infrastructure and LLM agent systems — built production platforms serving Microsoft and Google, and fine-tuned sub-billion parameter models to within 2% of GPT-4o-mini. Experienced across the full post-training stack: data collection, reward design, agent orchestration, and evaluation on Kubernetes.

Work Experience

DeccanAI

AI & Backend Engineer

Oct 2025 – Present|Hyderabad, India
  • Built a production RL platform (Python, FastAPI) for human-in-the-loop golden trajectory generation, coordinating 500+ annotators and driving $10M ARR.
  • Architected Stark-Forge, a distributed backend framework that runs isolated services on Kubernetes; added pluggable SQL, JSON, and Python verification services with support for multiple agent runtimes.
  • Designed evaluation and verification pipelines by defining success criteria and automated checks for SQL and code tasks, improving end-to-end task success rate from 41% to 68%.
  • Owned delivery of 20+ production MCP servers that generated verified execution traces; the Jira MCP server handles 10,000+ requests/day in production evaluation pipelines used by Microsoft and Google.
  • Fine-tuned Qwen-0.5B for text-to-SQL on Spider using Agent-Lightning, reaching within 2% of GPT-4o-mini accuracy with 3× smaller scale and 10× lower inference cost.

Deutsche Bank

Software Engineer

Jul 2024 – Oct 2025|Pune, India
  • Architected a RESTful ETL pipeline (Spring Boot, Airflow, SQL) automating 10,000+ alerts/day across financial workflows; reduced data load time by 40% and freed 3 ops engineers for higher-value work.
  • Engineered high-concurrency microservices with Memcached and Java ExecutorService for business-critical internal systems; reduced outages by 30% and improved P99 latency from 820ms to 310ms for 5,000+ daily users.

AiDash

Machine Learning Engineer Intern

Jan 2024 – Jul 2024|Bengaluru, India
  • Built a Python ML SDK abstracting Kubeflow and Airflow; compressed pipeline setup from 2 days to 3 hours, adopted by 12+ data scientists with 30% faster experiment cycles.
  • Developed a human-in-the-loop Annotation Service with QGIS for raster validation; eliminated 40% of manual GIS effort across 8 annotation campaigns.

Education

Indian Institute of Information Technology Allahabad

Bachelor of Technology in Electronics & Communication Engineering

CGPA: 8.80/10.0|Nov 2020 – May 2024

Technical Skills

AI & ML: Reinforcement Learning, LLMs, SFT, RLHF, Post-training, Fine-tuning, Reward Design, Evaluation
Agent Systems: LangChain, AutoGen, CrewAI, Agent-Lightning, MCP, Tool-use Agents, Multi-Agent Orchestration
ML Infra & Cloud: Kubeflow, Airflow, Distributed Training, Kubernetes, AWS, GCP, Docker, Jenkins, CI/CD
Languages: Python, Java, TypeScript, JavaScript, C/C++, SQL
Backend: FastAPI, Spring Boot, Django, REST APIs, Microservices
Databases: PostgreSQL, MySQL, Oracle, Memcached
Concepts: Distributed Systems, System Design, DSA, Async Processing, Data Pipelines