Senior Applied AI Forward Deployed Engineer

SAHJANAND BHUPENDRABHAI PATEL

Senior Applied AI & Forward Deployed Engineer

Decatur, AL(Central Time Zone) +1-650-***-****

*********.*************.*****@*****.***

linkedin.com/in/sahjanand-bhupendrabhai-patel-835139434

PROFESSIONAL SUMMARY

Client-facing Forward Deployed AI Engineer and Solutions Architect with 10

years of software engineering experience and 4+ years specializing in LLM

inference, fine-tuning, GPU infrastructure, and pre-sales field engineering.

Proven track record leading technical discovery, running load testing and

evaluations, and shipping hands-on-keyboard POCs directly inside enterprise

customer environments across AWS, Azure, and GCP. Deep technical expertise

in open-model serving frameworks (vLLM, SGLang, TensorRT-LLM), fine-tuning

methodologies (SFT, DPO, RFT), Python, and Kubernetes (K8s) orchestration.

Adept at bridging technical depth with executive presence—deep-diving with ML

engineers and presenting strategic trade-offs to VPs on the same day.

CORE COMPETENCIES & TECHNICAL SKILLS

● LLM Inference & Serving Frameworks: vLLM, SGLang, TensorRT-LLM,

Triton Inference Server, TGI, High-Throughput Serving, Latency

Benchmarking

● LLM Fine-Tuning & Alignment: Supervised Fine-Tuning (SFT), Direct

Preference Optimization (DPO), Reinforcement Fine-Tuning (RFT),

LoRA/QLoRA, PyTorch

● Field Engineering & Pre-Sales: Technical Discovery, Hands-on POC/MVP

Construction, Load Testing & Evals, Executive Presentations, Stakeholder

Management, Requirements Scoping

● Cloud, GPU & Infrastructure: Kubernetes (K8s), AWS, Azure, GCP, NVIDIA

GPU Infrastructure (H100, A100, L40S), Docker, Ray

● Software Development & Systems: Python, C/C++, CUDA, REST/gRPC

APIs, CI/CD, Product Feedback Loops

PROFESSIONAL EXPERIENCE

CareFirst — Remote

Lead Forward Deployed AI Engineer / Applied AI Architect

Jul 2023 – Present

● Led technical discovery sessions and pre-sales architecture reviews with

enterprise technical leads, ML teams, and VP-level executives to scope

requirements, model architectures, and deployment topographies.

● Built and deployed hands-on-keyboard POCs and production integrations

directly inside client enterprise environments, navigating customer security

constraints, VPC networking, and Kubernetes infrastructure.

● Guided enterprise clients through model selection, evaluation frameworks,

and fine-tuning strategies (SFT, DPO, RFT), successfully transitioning

clients from open-model exploration to production scale.

● Configured, benchmarked, and load-tested open-source LLM inference

stacks utilizing vLLM, SGLang, and TensorRT-LLM on multi-GPU

Kubernetes clusters across AWS, Azure, and GCP.

● Conducted rigorous evaluation and load testing suites to optimize p95/p99

latency, token throughput (TTFT, ITL), and GPU memory utilization under

peak enterprise loads.

● Managed multi-stakeholder relationships, identifying technical champions,

navigating enterprise procurement dynamics, and aligning cross-functional

teams to accelerate deal velocity.

● Synthesized recurring client deployment bottlenecks, framework gaps, and

field feedback to directly influence internal product and engineering

roadmaps.

Cognizant — Remote

Senior Field Solutions & Applied ML Engineer

Jan 2019 – Jun 2023

● Served as a forward-deployed engineer delivering customized machine

learning platforms and production services inside client cloud environments

(AWS, Azure, GCP).

● Architected containerized ML inference pipelines on Kubernetes using

Python, Docker, and REST/gRPC APIs, implementing automated failover

and scaling rules.

● Executed Supervised Fine-Tuning (SFT) and domain adaptation on

open-source language and vision models using PyTorch and distributed

GPU clusters.

● Run pre-sales discovery calls, technical demonstrations, and load-testing

benchmarks to validate system feasibility for client engineering leads and

decision-makers.

● Partnered with client security and infrastructure teams to ensure all

deployed software complied with strict enterprise security and data privacy

standards.

Dell Technologies — San Jose, CA

Software Engineer (Accelerated Systems)

Oct 2016 – Dec 2018

● Developed backend microservices and accelerated data processing

modules in Python and C++ for distributed high-performance computing

setups.

● Containerized multi-node applications using Docker and Kubernetes,

managing GPU resource allocation and memory bandwidth utilization.

● Automated build pipelines, benchmarking scripts, and cloud deployment

workflows across multi-cloud environments.

IBM — San Jose, CA

Systems Software Engineer

Jul 2013 – Sep 2016

● Authored backend Python scripts and C++ utilities for system monitoring,

log parsing, and automated data ingestion.

● Conducted system performance profiling, memory utilization analysis, and

Linux kernel optimization.

EDUCATION

Master of Science in Computer Science

The University of Texas at Austin — Austin, TX (2014 – 2016)

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