Senior Applied AI Engineer - India / Remote

Primary Responsibilities

• Design, build, and improve AI-powered capabilities that help customers understand, optimize, and control cloud, SaaS, and AI spend.
• Develop anomaly detection systems that identify unusual spending patterns, waste, and operational risks.
• Build forecasting models for consumption, budgets, cost trends, and capacity planning.
• Design recommendation and optimization engines that identify savings opportunities and rank actions based on expected business impact.
• Develop AI and ML models that improve recommendation relevance, prioritization, explainability, and customer trust.
• Analyze large-scale cost, usage, operational, and telemetry datasets to uncover trends and optimization opportunities.
• Design and implement feature engineering pipelines, experimentation frameworks, and analytical datasets.
• Fine-tune AI systems and agent behaviors to improve quality, consistency, explainability, and reliability.
• Build evaluation frameworks that measure model performance, recommendation quality, forecast accuracy, agent effectiveness, and business outcomes.
• Analyze and eliminate failure modes such as hallucinations, reasoning failures, excessive tool invocation, and agent loops.

Secondary Responsibilities

• Contribute to the design and implementation of autonomous and semi-autonomous FinOps agents.
• Build integrations with MCP servers, APIs, enterprise systems, and optimization workflows.
• Participate in multi-agent system design where specialized agents collaborate to solve customer problems.
• Contribute to the evolution of Mavvrik’s semantic layer, business entities, metadata models, and optimization concepts.
• Mentor engineers through code reviews, design reviews, experimentation practices, and technical guidance.
• Promote best practices around AI reliability, observability, governance, testing, and production readiness.

Qualifications

Required

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, Mathematics, Statistics, or a related field.
• 6–12 years of hands-on experience in software engineering, machine learning, data science, or applied AI product development.
• Strong programming skills in Python and software engineering fundamentals.
• Experience building production-grade AI, ML, analytics, or optimization systems.
• Strong experience with anomaly detection, forecasting, predictive analytics, recommendation systems, or optimization algorithms.
• Experience designing and implementing data pipelines for analytical and AI workloads.
• Experience with SQL and modern analytics platforms such as PostgreSQL, Snowflake, BigQuery, Databricks, or similar technologies.
• Experience deploying AI Systems on AWS, Azure, or GCP.
• Strong understanding of agent lifecycle management, memory, context management, tool orchestration, agent loops, and common agent failure modes.
• Strong understanding of RAG, embeddings, vector search, hybrid search, and reranking.
• Demonstrated experience using AI-assisted development tools as part of daily engineering workflows.
• Experience evaluating AI-generated code, analysis, recommendations, and designs to identify risks, inaccuracies, and hidden assumptions.
• Ability to independently drive initiatives from concept to production.

Preferred

• Experience building agentic AI systems, autonomous workflows, or AI copilots.
• Experience with MCP servers, tool orchestration, and at least one modern agentic AI framework such as LangGraph, CrewAI, AutoGen, Semantic Kernel, Mistral Agents, OpenAI Agents SDK, or similar orchestration frameworks.
• Experience implementing AI observability, governance, evaluation, and reliability practices.
• Experience contributing to semantic layers, business ontologies, metadata systems, knowledge graphs, or enterprise data models.
• Experience in FinOps, cloud cost management, SaaS management, AI cost management, observability, or enterprise technology management.
• Experience working in fast-paced startup environments.

What Success Looks Like

• Ships high-impact forecasting, anomaly detection, optimization, and recommendation capabilities that deliver measurable customer value.
• Improves recommendation quality, accuracy, explainability, and customer adoption over time.
• Builds robust evaluation frameworks and quality metrics that continuously improve AI system performance.
• Contributes to autonomous optimization agents that customers trust and rely on.
• Balances strong engineering rigor with rapid experimentation and delivery velocity.

Benefits

• Competitive salary, health insurance, and equity package
• Remote-first work environment
• Flexible working hours with overlap with US time zones
• Significant opportunity to influence AI strategy and technical direction
• Direct impact on company growth and customer outcomes
• Opportunity to work on an AI-driven cloud, SaaS, and AI cost management platform

About Mavvrik