|
|
| CLM-focused consultant with 17 years in Contract Lifecycle Management; 13 years delivering Conga CLM solutions for enterprise clients; experienced in requirements gathering, vendor selection, solution design, configuration, and change management; proficient in Salesforce, Conga tools, eSign integrations, and cross-module Salesforce implementations. |
|
Career Objectives:
Looking to help companies transform their Contract Management processes to a Digital platform with AI capabilities end to end.
|
|
|
|
|
| Forward Deployed Engineer with 4+ years of experience integrating AI models, data pipelines, and intelligent workflows into enterprise environments. Proficient in Python, SQL, and cloud infrastructure with hands-on ML Ops. |
|
Career Objectives:
Seeking opportunities in AI/ML engineering roles focusing on deploying production-grade AI systems.
|
|
|
|
|
| Seasoned CLM Product Owner with 17 years in CLM and 13 years in product ownership. Delivered 30+ CLM solutions, led vendor selection (iCertis, Conga, Malbek, IronClad), and guided end-to-end CLM implementations for major clients such as SanDisk, Nasdaq, VMware, McKesson, Nuance, Twitter, Open Society Foundation, Monster Energy, Nokia, and others. |
|
Career Objectives:
Looking to build the next generation of AI Native Contract Lifecycle Management (CLM) Solutions for any market.
|
|
|
|
|
| Accomplished consultant with 13+ years of experience in delivering projects in Supply Chain Management, Contract Lifecycle Management (CLM), Business Process Management and Data Warehousing. Roles included Project Manager, Business Analyst and solution consultant with strong stakeholder management and change management capabilities. |
|
Career Objectives:
Seeking a CLM Solution Architect role where I can apply 13+ years of hands-on CLM implementation experience — across Icertis, Agiloft, and enterprise platform integrations — to design scalable, AI-enabled contracting architectures. Aiming to bring proven expertise in cross-functional solutioning (Legal, Sales, Finance, Procurement) and a track record of measurable process improvement to help organizations modernize their contract lifecycle from quoting through order management.
|
|
|
|
|
| AI/ML Engineer with 3+ years of experience designing, deploying, and scaling production Machine Learning and Generative AI solutions for enterprise applications. Experienced in building LLM-powered applications, Retrieval-Augmented Generation (RAG) systems, Agentic AI workflows, AI microservices, and end-to-end MLOps pipelines. |
|
Career Objectives:
AI/ML Engineer focused on designing, deploying, and scaling production ML and Generative AI solutions for enterprise applications.
|
|
|
|
|
| Agentic AI Engineer with 4+ years of experience architecting and deploying autonomous LLM systems, Enterprise RAG pipelines, and multi-agent orchestration frameworks across financial services and telecom environments. |
|
Career Objectives:
Agentic AI Engineer focusing on architecting and deploying autonomous LLM systems, Enterprise RAG pipelines, and multi-agent orchestration.
|
|
|
|
|
| AI/ML Engineer with 4+ years of experience building and deploying production ML systems across financial services and enterprise software. Skilled in end-to-end pipelines, Generative AI, RAG systems, and multi-agent workflows using Python, PyTorch, LangChain, and Azure OpenAI. Experienced in scaling ML infrastructure on Spark and Databricks with strong MLOps and model governance practices. |
|
|
|
|
| Software Engineer with 2 years of experience deploying production AI systems, client-facing agentic workflows, and LLM integrations; strong background in full-stack development and DevOps. |
|
Career Objectives:
Pursuing roles in AI/ML engineering focusing on production AI systems and LangGraph integration.
|
|
|
|
|
| Generative AI Engineer with 3+ years of experience building and deploying production-grade LLM systems, RAG pipelines, and agentic AI frameworks across AWS, GCP, and Azure. Delivered AI solutions reducing manual effort by 60%+ in regulated enterprise environments. Pursued MS in Computer Science at University at Buffalo. |
|
Career Objectives:
To leverage Generative AI expertise in building production-grade LLM systems and scalable AI solutions across cloud platforms.
|
|
|
|
|
| Results-driven Data Engineer with 5 years of progressive experience architecting enterprise-scale ETL/ELT pipelines, big data platforms, and AI-powered analytics infrastructure across financial services and healthcare domains. |
|
Career Objectives:
Data Engineer focused on designing scalable ETL/ELT pipelines and cloud-based data platforms.
|
|
|
|
|
| Data Engineer with 4+ years of experience integrating data pipelines, AI models, and APIs into production systems across cloud environments; proficient in Python, SQL, PySpark, and modern data tooling. |
|
Career Objectives:
Seeking a data engineering role to design scalable data pipelines and AI-enabled data platforms in enterprise environments.
|
|
|
|
|
| Full-stack software engineer with expertise in Python/JavaScript, AWS Bedrock, and production-grade distributed systems; experienced in leading requirements, debugging issues, and delivering scalable, observable solutions. |
|
Career Objectives:
Customer-facing software engineer with 6+ years shipping production systems end to end in Python and JavaScript. Specialize in taking solutions from prototype to production - APIs, integrations, agentic / LLM workflows, and evaluation harnesses - with measurable reliability gains.
|
|
|
|
|
| Over 19 years of enterprise infrastructure experience specializing in multi-agent LLM orchestration, RAG pipeline design, MCP integration, and AWS Bedrock. |
|
Career Objectives:
Forward-deployed engineer and AI systems architect delivering enterprise-scale AI, multi-agent systems, and scalable infrastructure.
|
|
|
|
|
| Customer-facing Software Engineer with 3+ years of experience across enterprise B2B SaaS platforms. Expertise in authentication, OAuth 2.0, SSO, API reliability, observability, and scalable integrations. Strong background in AI tooling and cross-functional collaboration. |
|
Career Objectives:
Software engineer focused on enterprise authentication, OAuth 2.0, SSO, and API integration for B2B SaaS.
|
|
|
|
|
| 5+ years building production-grade AI and data systems across healthcare, insurance, and financial services; experience with LangChain, OpenAI API, RAG pipelines, Palantir Foundry; full-stack Python/TypeScript development; cloud infrastructure on AWS/Azure/GCP. |
|
Career Objectives:
Forward Deployed Engineer focused on AI/data systems with enterprise impact, leveraging LLM-powered workflows and scalable data pipelines.
|
|
|
|
|
| Senior Business Systems Solution Architect with 20+ years in CPQ implementations, CLM and Salesforce CRM administration. Led end-to-end Quote-to-Cash projects, integrations, and SOX ITGC compliance across multiple cloud platforms including Cloudflare, Samsara, and SurveyMonkey. |
|
Career Objectives:
Senior-level roles in CPQ/CLM with focus on delivering revenue recognition and successful implementations.
|
|
|
|
|
| AI Engineer with 4+ years designing and deploying production-grade Generative AI, LLMs, and agentic AI systems across pharmaceutical and retail domains. Expertise in RAG pipelines, LangChain/LangGraph, fast API microservices on AWS/Azure, and end-to-end ML lifecycle. |
|
Career Objectives:
Aspire to design and deploy scalable AI/ML systems, with a focus on Generative AI, LLMs, and multi-agent orchestration to accelerate enterprise drug development, regulatory processes, and clinical decision support.
|
|
|
|
|
| Consultant specializing in Contract Lifecycle Management (CLM) integrations, APIs, OOTB Adapters, Azure Service Bus, webhooks, and different means to connect CLM with other enterprise systems for contract streamlining. |
|
Career Objectives:
To contribute as CLM integration consultant leveraging API integrations and enterprise system connectivity.
|
|
|
