Mavvrik
Senior Applied AI Engineer
- Compensation
- Not disclosed
- Location
- Not listed
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 6+ years
- Category
- Ai engineering
- Posted
Skills
Must have
- 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.
Nice to have
- 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 orchest
- 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.
Full description
Mavvrik is looking for a Senior Applied AI Engineer with 6–12 years of experience who combines strong software engineering capabilities with expertise in applied AI, machine learning, analytics, and optimization systems.
This is a senior individual contributor role focused on building the intelligence layer that powers cloud, SaaS, and AI cost optimization capabilities, including forecasting, anomaly detection, recommendation systems, optimization models, and autonomous agents.
The ideal candidate combines strong software engineering skills with deep experience in applied AI, machine learning, data analytics, and optimization systems. You actively leverage AI-assisted development platforms and agentic workflows to improve velocity while applying strong technical judgment.
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.