2 days ago
Mumbai, IndiaStaff+
Responsibilities
- Assess legacy reports, operational processes, pain points, and automation opportunities with stakeholders.
- Prioritize solutions based on business value, feasibility, risk, and reuse potential.
- Develop Python-based automations, data-processing workflows, APIs, and scheduled solutions.
- Build LLM-powered applications for extraction, summarization, classification, knowledge retrieval, and recommendation generation.
- Integrate tools, files, databases, APIs, and cloud services while maintaining quality, security, controls, and auditability.
- Deploy, document, monitor, support, and scale reusable production solutions.
- Drive user adoption and measure improvements in effort, cycle time, quality, and reliability.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or a related field is required; a master’s degree is a plus.
- At least 5 years of relevant experience in software development, automation engineering, data engineering, analytics engineering, AI solutions, or a comparable technical role.
- Demonstrated experience delivering automation or AI solutions into production and supporting them after release.
- Strong hands-on Python proficiency, including object-oriented programming, data processing, package design, and maintainable coding practices.
- Practical experience building LLM applications or automations, including prompt design, grounding, evaluation, and safe model-output use.
- Experience with structured and unstructured data, data modeling, SQL, Python data libraries, REST APIs, and multi-system integrations.
- Experience with Git, code reviews, Pytest or comparable testing frameworks, CI/CD practices, logging, exception handling, and production support.
- Working knowledge of cloud solutions, preferably Microsoft Azure, and enterprise AI services such as Azure OpenAI.
- Strong analytical, debugging, problem-solving, stakeholder communication, documentation, ownership, and prioritization skills.
- Preferred experience includes RAG, vector databases, semantic search, LangChain, Power Automate, Power BI, Terraform, Pulumi, Docker, Kubernetes, observability tools, GitHub Copilot, responsible AI, privacy, access controls, data governance, and enterprise security requirements.
Benefits
- Flexible working environment.
- Volunteer time off.
- LinkedIn Learning.
- Employee Assistance Program (EAP).