[Remote] Sr. Developer
Note: The job is a remote job and is open to candidates in USA. Mphasis is hiring a Developer, AI Vibe Coding & Engineering to design, build, and operate production AI systems end to end. The role spans machine learning, deep learning, generative AI, data pipelines, MLOps, cloud deployment, and collaboration with cross-functional stakeholders to deliver observable, evaluable, and safe AI capabilities.
Responsibilities
- Design, train, evaluate, and ship machine learning and deep learning models (classification, regression, ranking, vision, NLP, time series) against well-defined business and scientific problems
- Design and implement LLM-powered applications using major model providers (Claude/Anthropic, Azure OpenAI, OpenAI, or equivalents)
- Build retrieval-augmented generation (RAG) systems, including chunking strategies, embeddings, vector store selection (e.g., Azure AI Search, pgvector), and re-ranking
- Develop agentic workflows with tool use and orchestration; implement guardrails, evaluation harnesses, and human-in-the-loop review where appropriate
- Apply prompt engineering, fine-tuning, and structured output techniques; measure quality with offline evals and online metrics
- Build and maintain robust data and feature pipelines on Azure; ensure data quality, lineage, and reproducibility
- Productionize models with sound MLOps practices: versioning, automated retraining, drift detection, and rollback strategies
- Use AI coding assistants (Claude Code, Cursor) effectively alongside traditional manual coding — choosing the right approach for each task and reviewing AI-generated code with rigor
- Manage source code in Git using a clean branching strategy and pull-request-based review
- Build and maintain CI/CD pipelines (e.g., Azure DevOps, GitHub Actions) for automated testing, packaging, and deployment of AI services
- Deploy and operate services on Azure using containers (Docker), orchestration (Kubernetes/AKS), and infrastructure-as-code (Terraform or Bicep)
- Instrument AI systems with logging, tracing, and evaluation pipelines so that quality, latency, and cost can be observed and managed over time
- Partner with security and compliance to address data privacy, PHI/PII handling, prompt injection, and model risk in regulated contexts
- Work directly with product, scientific, and business stakeholders to scope problems, set realistic expectations, and choose the right level of AI sophistication for the job
- Mentor engineers on AI-assisted development practices and on the patterns and pitfalls of LLM-based systems
- Conduct rigorous design and code reviews; advocate for evaluation, safety, and observability as first-class concerns
Skills
- Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, Mathematics, Statistics, or a related field — or equivalent practical experience
- 4 + years of professional software engineering experience, with at least 2 years building and shipping ML or AI systems in production
- Strong proficiency in Python and core ML libraries (PyTorch and/or TensorFlow, scikit-learn, pandas, NumPy)
- Hands-on experience deploying LLM-based applications using major model providers (Anthropic Claude, Azure OpenAI, OpenAI, or open-source models)
- Practical RAG and embeddings experience, including at least one production vector store
- Demonstrated proficiency with AI coding tools such as Claude Code and Cursor, balanced with strong manual coding fundamentals
- Solid command of Git, branching strategies, and pull-request-based code review
- Hands-on experience building and operating CI/CD pipelines (e.g., Azure DevOps, GitHub Actions) for production workloads
- Hands-on experience deploying services on Azure (AKS, App Service, Functions, Azure AI/ML services, or similar) and with containerization (Docker)
- Strong written and verbal communication; able to explain modeling decisions and trade-offs to non-technical stakeholders
- Proven ability to thrive in a fully remote, globally distributed team
Benefits
- Fully remote work arrangement
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