PDSSOFT INC.

Manage IT projects with cross-functional teams using Agile and Waterfall methodologies including planning, execution, risk, budget, and stakeholder management. | Requires 0.5-12 years IT experience with at least 3 years project management, cross-functional team coordination, and skills in Agile, Waterfall, risk, budget, and scope management. | Project Manager Dearborn,MI JD :Bachelor's degree in Computer Science, Information Technology, Engineering, Business Administration, or a related field .5–12 years of overall IT experience with at least 3 years of Project Management experience .Experience working with cross-functional and geographically distributed teams .Project Planning & Execution Stakeholder Management Risk & Issue Management Budget & Resource Management Agile (Scrum/Kanban) and Waterfall methodologies Scope & Change Management

Develop and maintain .NET Core microservices and REST APIs with AI-assisted software development on Azure platform. | Strong C#/.NET Core skills, microservices and REST API experience, AI-assisted development knowledge, and Azure cloud expertise. | Software Engineering with AI Location: Redmond,WA ( Open for Remote) Skills Required: • Strong C# / .NET Core development • Microservices and REST API development • Hands-on experience with AI-assisted / agentic software development • HyperScaler cloud experience (Azure preferred) • • Solid experience in Azure & Microsoft ecosystem

Develop and design commerce tools and solutions using CommerceTool platform and APIs. | Requires 4+ years software engineering with eCommerce knowledge, 5+ years CommerceTool experience, API and microservices expertise, and strong communication skills. | Commerce Tool Developer Location : Plano,TX / WFH USC/GC preferred Job Description: 5+ years of working in CommerceTool platform. · 4 + years Software Engineering and a deep understanding of the eCommerce industry? (SSE/ PSE) · 2 + years Software Engineering and a deep understanding of the eCommerce industry? (SE) · 1 + Years of Experience with web service APIs working with either REST, GraphQL or both · Experience building with REST APIs, Microservices, preferably in a commerce industry · The ability to weigh trade-offs through discussions working within a cross-functional team · Experience is Headless and MACH Architecture framework preferred, not mandatory · Experienced in solution development, Assist in Solution Designing, project scoping and excellent product demonstration skills · Excellent communicator and presenter able to gain audience confidence · Hands-on, high-energy, passionate and creative problem solver with know how to get things done and ability to lead others to success · Ability to build a deep understanding of a customer's communications needs and guide them to a technical solution · Familiarity with cloud platforms (Azure, Google Cloud) · Understanding of Enterprise Product Catalogue is good to have · Suggestions: Some extra commerce Tool platform experience should be there 2+ on dev and some CT architecture understanding

Develop and optimize advanced fine-tuning and prompt engineering techniques for LLMs specific to utility domain, and collaborate on model deployment and monitoring. | Proficiency in PyTorch/TensorFlow, advanced LLM training, GPU hardware knowledge, LLMOps experience, and ability to adapt research techniques to production. | GenAI/LLM Engineer Location: Remote Duration: Long Term Job Description: • Implement and optimize advanced fine-tuning approaches (LoRA, PEFT, QLoRA) to adapt foundation models to PG&E's domain • Develop systematic prompt engineering methodologies specific to utility operations, regulatory compliance, and technical documentation • Create reusable prompt templates and libraries to standardize interactions across multiple LLM applications and use cases • Implement prompt testing frameworks to quantitatively evaluate and iteratively improve prompt effectiveness • Establish prompt versioning systems and governance to maintain consistency and quality across applications • Apply model customization techniques like knowledge distillation, quantization, and pruning to reduce memory footprint and inference costs • Tackle memory constraints using techniques such as sharded data parallelism, GPU offloading, or CPU+GPU hybrid approaches • Build robust retrieval-augmented generation (RAG) pipelines with vector databases, embedding pipelines, and optimized chunking strategies • Design advanced prompting strategies including chain-of-thought reasoning, conversation orchestration, and agent-based approaches • Collaborate with the MLOps engineer to ensure models are efficiently deployed, monitored, and retrained as needed • Deep Learning & NLP: Proficiency with PyTorch/TensorFlow, Hugging Face Transformers, DSPy, and advanced LLM training techniques • GPU/Hardware Knowledge: Experience with multi-GPU training, memory optimization, and parallelization strategies • LLMOps: Familiarity with workflows for maintaining LLM-based applications in production and monitoring model performance • Technical Adaptability: Ability to interpret research papers and implement emerging techniques (without necessarily requiring PhD-level mathematics) • Domain Adaptation: Skills in creating data pipelines for fine-tuning models with utility-specific content "