Engineer Jobs

About The Position

Requirements

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.
• 5+ years of experience in software engineering or full-stack development.
• Hands-on experience with Generative AI technologies and LLMs (e.g., OpenAI, Anthropic, Gemini).
• Strong experience with prompt engineering, RAG pipelines, and agent-based AI systems.
• Proficiency in Python and JavaScript/TypeScript.
• Experience with modern front-end frameworks (React, Angular, or Vue).
• Experience with APIs, microservices architecture, and system integrations.
• Familiarity with vector databases and embedding-based systems.
• Experience with cloud platforms (AWS, GCP, or Azure).
• Strong foundation in data structures, algorithms, and system design.

Nice To Haves

• Experience with model fine-tuning, training, and evaluation workflows.
• Familiarity with deep learning frameworks such as PyTorch or TensorFlow.
• Experience with agent frameworks such as LangChain, LangGraph, or LlamaIndex.
• Knowledge of AI governance, risk, and compliance frameworks.
• Experience leading engineering teams or delivering client-facing AI solutions.
• Cloud or AI/ML certifications (AWS, Azure, or GCP).

Responsibilities

• Design, develop, and optimize prompts, chains, and workflows for LLM-based applications.
• Build and manage RAG pipelines, including ingestion, preprocessing, chunking, embeddings, indexing, retrieval, and evaluation.
• Architect and implement agentic AI systems, including multi-step reasoning, tool usage, orchestration, and multi-agent patterns.
• Establish prompt evaluation frameworks, benchmarking processes, and continuous improvement loops for quality, latency, and cost.
• Apply fine-tuning and domain adaptation techniques where necessary.
• Ensure responsible AI practices, including governance, safety, and reliability in production environments.
• Design and build scalable backend systems using Python (FastAPI or similar) and/or Java-based architectures.
• Develop modern front-end applications using React, Angular, or Vue frameworks.
• Build and maintain APIs, microservices, and integrations across internal and external systems.
• Ensure system performance, scalability, observability, and reliability across the stack.
• Contribute to architectural decisions and long-term technical roadmap development.
• Design and manage data pipelines (ETL) to support AI workflows and model performance.
• Implement and maintain vector databases and embedding-based retrieval systems.
• Deploy, monitor, and optimize AI models in production environments.
• Optimize inference performance, scalability, and cost efficiency.
• Leverage cloud platforms (AWS, GCP, Azure) and AI services such as Vertex AI.
• Translate business requirements into scalable architectures, technical specifications, and delivery plans.
• Lead development efforts, including system design, code reviews, and engineering best practices.
• Mentor team members and promote a culture of engineering excellence and AI adoption.
• Collaborate cross-functionally with product, operations, and leadership teams to deliver impactful AI solutions.
• Evaluate emerging AI tools, frameworks, and technologies for practical implementation.
• Develop and implement testing strategies across application and AI layers, including unit, integration, regression, and performance testing.
• Maintain CI/CD pipelines and ensure production readiness of all systems.
• Monitor system performance, manage incidents, and drive continuous optimization.
• Ensure high standards of reliability, scalability, and consistency across releases.
• Ensure all AI systems, data pipelines, and integrations comply with HIPAA and organizational data security standards.
• Implement safeguards for handling Protected Health Information (PHI), including encryption, access control, and secure transmission.
• Establish audit trails, monitoring systems, and governance frameworks for AI usage and data handling.
• Conduct risk assessments related to AI systems, data exposure, and model behavior.
• Collaborate with compliance and security teams to enforce best practices in data protection and AI governance.

Benefits

• Paid Time Off (PTO)
• Paid Holidays
• Volunteer Time Off
• Bereavement Leave
• Comprehensive Medical Coverage
• Flexible Spending Accounts (FSAs) and wellness-related benefits
• Disability Insurance
• Employee Assistance Program (EAP)
• 401(k) Retirement Plan
• Role-based Stipends
• Professional Development and Continuing Education Support
• Employee Discounts
• Team Events and Offsites
• Career Growth and Advancement Opportunities