Forward Deployed Engineer

AI/ML Engineer (Contract)

Stealth AI Startup, Hybrid

• Leading development of an Automated Valuation Model (AVM) from inception to its current production-ready stage on a 4-person team — estimating a home's appraised value from its address so lenders can skip physical appraisals on standard, low-risk properties.
• Own the full ML lifecycle from data to deployment: cleaned ~38k subject–comp appraisal pairs, engineered 60+ features, built live RentCast API ingestion and a condition/quality scoring service, and shipped comparable-selection and condition-based triage logic with LightGBM training and evaluation.
• Achieved 5.1% MAPE with 68% of valuations within ±5% on a production-shaped holdout using live API data only — less than half the 11.5% MAPE of the data vendor's own AVM.

Forward Deployed AI Engineer

SBL, Remote

• Deployed RevOps and workflow-automation solutions for enterprise and growth-stage clients (Emoha, India eldercare; Topmate, 300K+-creator platform; Clinik), owning delivery from discovery to production.
• Built lead-enrichment and outbound automation on SBL's RevOps platform (Konduit) that replaced manual prospecting research for clients and lifted outbound response rates by 6–8%, improving customer-acquisition conversion.
• Partnered with Emoha to map end-to-end sales and acquisition workflows and embed automation with human-in-the-loop checkpoints, reducing manual handoffs.
• Resolved production issues across multiple concurrent client rollouts (integration failures, CRM sync, lead-source gaps), keeping client deployments reliable.

AI Engineer & Fractional Developer

AnternData Solutions, Bangalore, India

• Delivered client-facing AI/ML and software projects end-to-end for global tech companies including TigerData (formerly Timescale, the $1B+ database company), from requirements through deployment and iteration.
• Built production-ready apps, reference architectures, and POC demos that accelerated developer adoption of customer platforms.
• As a fractional developer, delivered technical demos and content that drove adoption of customer platforms.

RealDataAgentBench

• LLM agent evaluation framework — a benchmark of 1,412+ scored runs across 12 frontier LLMs on 39 real data-science tasks, scoring correctness, code quality, efficiency, and statistical validity with per-run cost tracking and 95% confidence intervals.
• Surfaced the core reliability gap (0.84–0.99 correctness vs. 0.52–0.90 statistical validity) and found gpt-4.1-mini statistically tied with top-ranked gpt-4.1 at 65× lower cost per task; these findings power CostGuard's routing engine.

CostGuard

• LLM reliability and cost proxy that intercepts calls, validates responses with RDAB-derived scoring, and retries or falls back across 12 models and 5 providers — with per-call cost tracking that surfaced routing decisions cutting spend 10–20× vs. GPT-4o defaults.
• Per-provider circuit breakers, a production-trace replay endpoint with 95% bootstrap CIs, Prometheus/Grafana observability, rate limiting, and a six-type alerting engine over Slack and webhooks; 90+ unit tests.

RelayOps

• Production-shaped telecom support agent with deterministic access control, scoped tools, tiered intent routing, hybrid RAG with citations, and guardrails blocking invented offers and PII — validated with adversarial evals (1.000 safe-route on a 100-case suite; zero billing escapes).

Tether & LoRA fine-tuning

• Tether: a durable execution layer (checkpoint/resume, cross-provider failover) for long-running LLM agents.
• LoRA fine-tune of DeepSeek-R1-Distill-Qwen-1.5B reaching 58.2% on GSM8K with 98.8% fewer trainable parameters.

M.S. Computer Science

Sacred Heart University, Fairfield, CT

• GPA: 3.8/4.0
• Upsilon Pi Epsilon (UPE) Honor Society

B.Tech Information Technology

GMR Institute of Technology, Vizianagaram, India

• GPA: 8.30/10