Senior Applied AI Engineer

Mavvrik; United States; Remote; USD 180,000 - 260,000; Full time

Benefits offered by this job

Remote-first

Health insurance

Equity package

Flexible hours

Job summary

Mavvrik is seeking a Senior Applied AI Engineer to help build the intelligence layer powering cloud, SaaS, and AI cost management. The role emphasizes production-grade AI, analytics, and optimization across forecasting, anomaly detection, and autonomous agents.

The candidate will work on AI-driven platforms, leverage agentic workflows, and contribute to FinOps capabilities. Remote-first environment with overlap across US time zones.

Qualifications

• Bachelor’s or Master’s degree in CS, DS, AI, Eng, Math, Stats, or related field.
• 6–12 years of hands-on software engineering, ML, DS, or applied AI.
• Proficient in Python and software engineering fundamentals.
• Experience building production-grade AI, ML, analytics, or optimization systems.
• Experience with anomaly detection, forecasting, and recommender/optimization algorithms.
• Experience designing data pipelines for analytical/AI workloads.
• Experience with SQL and analytics platforms (PostgreSQL, Snowflake, BigQuery, Databricks).
• Experience deploying AI systems on AWS, Azure, or GCP.
• Knowledge of agent lifecycle, memory/context management, tool orchestration, agent loops, failure modes.
• Understanding of RAG, embeddings, vector search, hybrid search, reranking.
• Experience evaluating AI-generated code and recommendations.

Responsibilities

• Design and build AI-powered capabilities for cloud, SaaS, and AI spend optimization.
• Develop anomaly detection systems for spending patterns and risks.
• Build forecasting models for consumption, budgets, and capacity planning.
• Design and optimize engines to identify savings opportunities.
• Develop AI/ML models to improve recommendation relevance and explainability.
• Analyze large-scale cost and telemetry datasets to uncover trends.
• Implement feature engineering pipelines and experimentation frameworks.
• Fine-tune AI systems and agent behaviors for reliability.
• Build evaluation frameworks for model performance and business outcomes.
• Eliminate failure modes such as hallucinations and agent loops.

Skills

Python programming

Software engineering fundamentals

Anomaly detection

Forecasting

Analytics

Optimization systems

Experimentation practices

AI-assisted development

Independent initiative

Data pipelines

Education

Bachelor’s or Master’s degree in CS/DS/AI/Engineering/Math/Stats

Tools

PostgreSQL

Snowflake

BigQuery

Databricks

LangGraph

CrewAI

AutoGen

Semantic Kernel

OpenAI Agents SDK

Mistral Agents

Job 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.

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

Mavvrik is a VC‑backed, AI‑driven startup revolutionizing hybrid cloud cost, SaaS cost, and AI cost management. Our platform empowers businesses to gain visibility, control, and optimization of their technology spend with real‑time precision.

If you are passionate about building intelligent optimization systems and believe AI can fundamentally improve how organizations manage technology investments, this is your opportunity to help shape the future of cloud FinOps at Mavvrik.

Learn more at www.mavvrik.ai.