Bidgely (which means "electricity" in Hindi) is an AI-powered SaaS Company accelerating a clean energy future by enabling energy companies and consumers to make data-driven energy-related decisions Ranked #7 in Applied AI on Fast Company’s list of Most Innovative Companies in the World, Bidgely is putting customers at the center of the clean energy future

What We Do

Powered by our unique patented technology, Bidgely's UtilityAI™ Platform transforms multiple dimensions of customer data - such as energy consumption, demographics, and interactions into deeply accurate and actionable consumer energy insights. We leverage these insights to empower each customer with personalized recommendations tailored to their individual personality and lifestyle, usage attributes, behavioral patterns, purchase propensity and beyond.

How We Do It

From a distributed energy resources (DER) and grid edge perspective, Bidgely is advancing smart meter innovation with data-driven solutions for solar PVs, electric vehicle (EV) detection, EV behavioral load shifting and managed charging, energy theft, short-term load forecasting, grid analytics and time of use (TOU) rate designs. Bidgely’s UtilityAI™ energy analytics provides deep visibility into generation and consumption for better peak load shaping and grid planning and delivers targeted recommendations for new value-added products and services.

You are a seasoned engineer with demonstrated expertise in Generative AI, Agentic systems, LLM orchestration, and distributed ecosystems. You have a proven track record of delivering production-grade AI systems at scale, leading technical teams by example, and driving innovation in the GenAI and Agentic space for your prior organization. You thrive in ambiguity, make strategic technical decisions, and mentor engineers to achieve excellence.

What You'll Do

• Define technical vision and architecture: Lead the design and architecture of scalable, production-grade GenAI systems using LangChain, LangGraph, FastAPI, and modern AI frameworks.

• Make critical technical decisions that balance innovation, scalability, and maintainability

• Drive GenAI innovation: Research, prototype, and implement cutting-edge GenAI techniques including advanced prompt engineering, RAG optimization, agentic AI systems, fine-tuning, and multi-agent orchestration

• Lead AI experimentation and evaluation: Design and implement comprehensive evaluation frameworks for LLM performance, establish best practices for prompt engineering, and drive data-driven decision making through rigorous experimentation

• Own GenAI at utility and program scale: Architect and optimize LLM workloads that support millions of calls across multiple utilities and channels, under strict cost and latency targets.

• Architect event-driven AI systems: Design and implement sophisticated event-driven architectures using SQS, asynchronous workflows, distributed processing, and microservices patterns

• Establish GenAI best practices: Define and enforce coding standards, design patterns, testingstrategies, and operational excellence for GenAI applications. Champion observability, monitoring, and reliability

• Technical leadership and mentorship: Mentor and guide engineers across all levels, conduct architecture reviews, provide technical direction, and foster a culture of continuous learning and innovation

• Cross-functional collaboration: Partner with product management, data science, engineering leadership, and business stakeholders to translate business requirements into technical solutions.

• Communicate complex technical concepts to diverse audiences

• Drive strategic initiatives: Identify opportunities for AI-driven innovation, evaluate emerging technologies, and lead proof-of-concept projects that align with business objectives

• Ensure production excellence: Establish SLAs, implement monitoring and alerting, optimize performance and cost, and ensure high availability of AI services

• Thought leadership: Represent Bidgely in the GenAI community through technical blogs, conference talks, open-source contributions, and industry engagement

What Makes You Successful

• Education: BS/MS+ in Computer Science, AI/ML, or equivalent from premier institutes

• Experience: 5+ years of software engineering experience with at least 1-2 years focused on

• Generative AI, Agentic AI, and production LLM-based applications

• Expert-level knowledge of LangChain, LangGraph, and LLM orchestration frameworks; deep, understanding of prompt engineering, RAG architectures, agentic AI, and multi-agent systems

• Production AI Systems: Proven track record of architecting and deploying production-grade AI systems at scale, handling millions of requests and complex workflows

• API & Microservices: Extensive experience building scalable RESTful APIs, microservices architectures, and event-driven systems using FastAPI, Flask, or similar frameworks

• LLM Integration: Deep expertise integrating and optimizing LLM providers; understanding of model selection, cost optimization, and latency management

• Technical Leadership: Demonstrated ability to lead technical teams, drive architectural decisions, and mentor engineers; experience with code reviews, technical design documents, and cross-team collaboration

• Problem Solving: Exceptional problem-solving skills with ability to tackle ambiguous, complex challenges; strong in algorithms, data structures, and system design

• Communication: Outstanding communication skills; ability to influence technical direction, present to leadership, and collaborate effectively across global distributed teams

Preferred Qualifications

• Python & Architecture: Expert-level Python programming with deep knowledge of software architecture, design patterns, distributed systems, and performance optimization

• Experience with vector databases (ChromaDB, Pinecone, Weaviate, FAISS) and advanced retrieval techniques

• Deep knowledge of LLM observability tools (LangSmith, Langfuse, Weights & Biases) and evaluation frameworks

• Expertise in AWS services (Bedrock, SQS, S3, Lambda, ECS, Parameter Store) and cloud-native architectures

• Experience with fine-tuning, RLHF, prompt optimization techniques, and model evaluation methodologies

• Knowledge of PostgreSQL optimization, Redis caching strategies, and database performance tuning

• Experience with Docker, Kubernetes, Terraform, and infrastructure-as-code

• Background in building conversational AI, chatbots, or virtual assistants

• Experience with MLOps, model deployment pipelines, and A/B testing frameworks

• Familiarity with emerging AI trends: multi-modal models, reasoning models, agent frameworks Diversity, Equity, Inclusion and Equal Opportunity

At Bidgely

we’re on a mission to make a difference and build a workplace where every unique voice is heard and celebrated. Here, we believe that celebrating the unique backgrounds, perspectives and abilities of every employee makes an impact not only for our company internally but also for our clients, customers and community. We are an equal opportunity employer and believe that the inclusive atmosphere we build together will enable every person to grow, contribute and thrive. Our hiring decisions are based on your skills, talent, and passion – not on your background, gender, race, age, or the quirky way you dance at office parties.