Senior Software Engineer

tration, retrieval augmentation (RAG) solutions and context-management pipelines for industrial use cases.

• Develop scalable and secure solutions which utilize an GenAI based solution underneath to improve internal software systems.

• Optimize LLM inference performance, token usage, latency, and model selection based on functional and cost constraints.

• Implement validation frameworks for LLM outputs, including rule-based, statistical, or semantic validation, alignment checks, and performance monitoring.

• Support or lead development of ML models (classification, regression, anomaly detection, time-series insights) for reliability, operations, and maintenance use cases.

• Collaborate with data scientists to convert analytical logic into stable production code and cloud-ready services.

• Develop pipelines integrating historian/SCADA/CMMS/APM datasets into AI workflows.

Software Engineering & Integration

• Engineer robust backend services in Python with clean architecture, modular design, and high-quality code practices.

• Build and maintain REST APIs, microservices, and integration points with industrial systems and enterprise platforms.

• Work with product and domain teams to embed AI/LLM features directly into industrial software applications.

• Contribute to UI/UX workflows (optional) for AI-driven features such as chatbot interfaces, AI copilots, or operator assistance tools.

Quality, Validation & Governance

• Design automated evaluation frameworks for LLM results: hallucination checks, accuracy scoring, domain constraint validation, and response explainability.

• Maintain experiment tracking, version control, and model documentation to ensure reproducibility and governance.

• Support secure handling of operational and proprietary data with compliance to organizational and industry standards.

• Conduct performance testing, error monitoring, and continuous improvement of deployed AI services.

Collaboration & Innovation

• Partner closely with domain SMEs (maintenance, reliability, operations) to translate use cases into AI-driven workflows.

• Collaborate with platform/cloud engineering teams to deploy LLM services at scale (containers, serverless, GPU-enabled workloads).

• Actively explore new LLM capabilities, vector databases, fine-tuning methods, and industrial AI patterns, driving innovation in the team.

• Mentor junior developers and support internal AI capability-building initiatives.

Required Skills & Experience

• 5-8+ years of professional software engineering experience, including 2-3+ years building AI/ML or LLM-driven applications in production environments.

• Strong expertise in Python with deep experience in backend development, RESTful API design, and microservices architecture.

• 3+ years of hands-on experience with FastAPI, including strong knowledge of its architecture, performance optimization, dependency injection, and asynchronous capabilities.

• Demonstrated experience developing and deploying LLM-powered applications using frameworks such as OpenAI, Hugging Face, LangChain, LlamaIndex, or similar ecosystems.

• Proven ability to design and implement LLM validation frameworks, evaluation methodologies, guardrails, and prompt governance pipelines to ensure reliability, accuracy, and compliance.

• Solid understanding of LLM fundamentals, including tokenization, transformer architecture, attention mechanisms, embeddings, fine-tuning approaches, model constraints, and context window management.

• Experience managing the end-to-end ML lifecycle, including data preparation, model training, packaging, deployment, versioning, monitoring, and performance optimization.

• Familiarity with industrial or operational data systems (e.g., APM, historian systems, SCADA, CMMS/EAM) is highly desirable.

• Strong working knowledge of CI/CD practices and DevOps tooling, including Jenkins, Docker, Kubernetes, and Helm.

• Experience deploying and scaling applications on AWS, including infrastructure design and cloud-native architecture.

• Excellent analytical, problem-solving, and communication skills with the ability to collaborate effectively across engineering, product, and business teams.

• Exposure to frontend technologies such as Angular is a plus.

Education Qualification

• Bachelor's Degree in Computer Science or "STEM" Majors (Science, Technology, Engineering and Math) with advanced experience.

Additional Information

Relocation Assistance Provided: Yes