Senior AI Engineer I

Jeppesen ForeFlight is redefining the future of aviation technology – equipping pilots, operators, and decision\-makers with the software tools to forge bold new digital paths that push past the expected. We stand with those who dream bigger, fly farther, and seek to explore the next frontier in the cockpit and operations center. Our Bengaluru team is a core part of our global engineering and operations hub, driving innovation for millions of aviation professionals worldwide. **Position Summary** We are seeking a highly accomplished **Senior AI Engineer / AI Architect** with deep experience in designing, building, and operationalizing intelligent systems that combine machine learning, generative AI, software architecture, and scalable cloud\-native engineering. The ideal candidate will demonstrate the mindset and rigor of an AI architect: able to frame complex problems, design reliable AI systems, evaluate trade\-offs, orchestrate model and tool interactions, ensure safety and governance, and deliver enterprise\-grade solutions from concept to production. This role requires a strong balance of architecture, applied AI, experimentation, and engineering discipline. The candidate should be capable of leading end\-to\-end AI solution design, including data strategy, model strategy, integration design, evaluation frameworks, workflow orchestration, deployment patterns, and operational monitoring. **Position Responsibilities** * Architect end\-to\-end AI systems that align business objectives, technical constraints, security requirements, and operational realities. * Design intelligent workflows that support reasoning, planning, task decomposition, retrieval augmentation, tool use, and multi\-step execution. * Define system patterns for AI applications, including prompt\-driven workflows, model routing, fallback strategies, context management, and state handling. * Develop innovative approaches for knowledge discovery, classification, prediction, ranking, anomaly detection, and pattern extraction across structured and unstructured data. * Build and optimize multimodal AI solutions involving **text, image, and tabular data** for advanced analytics and decision\-making use cases. * Design robust evaluation frameworks for AI systems, including offline testing, benchmark creation, quality scoring, red teaming, regression testing, and human\-in\-the\-loop validation. * Apply strong software architecture principles to ensure modularity, observability, maintainability, scalability, and fault tolerance of AI systems. * Lead the design of secure AI integrations with APIs, enterprise data sources, workflow engines, and external tools. * Develop and maintain scalable data pipelines, feature pipelines, and model pipelines supporting training, inference, and continuous improvement. * Use cloud and distributed computing platforms to support model development, orchestration, deployment, and monitoring at enterprise scale. * Apply statistical analysis and experimental methods to interpret results, validate hypotheses, measure improvements, and quantify model uncertainty. * Establish model lifecycle processes covering versioning, traceability, reproducibility, testing, deployment, rollback, and monitoring. * Collaborate closely with software engineers, data engineers, product teams, and stakeholders to define architecture, requirements, and implementation plans. * Demonstrate proven product experience in designing and delivering **agentic workflows, AI workflow orchestration, RAG\-based architectures, and agentic coding solutions**. * Conduct proof\-of\-concepts for emerging tools, frameworks, and methods, and determine production readiness based on architectural, security, and performance criteria. * Create clear technical documentation, architecture diagrams, decision records, experiment summaries, and executive\-ready updates. * Monitor AI system behaviour, data drift, model quality, latency, throughput, and operational reliability to ensure service\-level expectations are met. * Mentor junior AI engineers and data scientists on architecture patterns, implementation practices, evaluation methods, and responsible AI principles. * Present technical work internally and externally through design reviews, workshops, technical forums, and conferences. * Contribute to innovation through patents, invention disclosures, and reusable technical assets. * Ensure AI solutions adhere to responsible AI standards, including safety, transparency, fairness, privacy, governance, and compliance. * Drive software development teams using a structured **spec\-driven development (SDD)** approach, with strong emphasis on clear specifications, implementation traceability, testing rigor, and delivery quality. * Support and guide teams in **agentic coding workflows**, including AI\-assisted development, code generation, code review support, debugging assistance, and automated test creation. **Basic Qualifications** * Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative discipline. * 10\+ years of overall relevant professional experience. * 5\+ years of experience in Data Science, AI Engineering, ML Engineering, or AI Architecture roles. * Proven experience designing and delivering production\-grade AI systems. * Strong foundation in machine learning, deep learning, statistical modeling, and experimental design. * Practical experience with NLP, computer vision, multimodal AI, generative AI, or reinforcement learning. * Proficiency in Python, R, Java, or equivalent languages used in AI and software engineering. * Strong software architecture and system design skills, including distributed systems and service integration. * Experience with cloud\-native AI/data platforms and scalable infrastructure. * Demonstrated ability to define evaluation strategies and quality metrics for AI systems. * Excellent communication, documentation, presentation, and stakeholder management skills. * Ability to work effectively in global, cross\-functional, and distributed teams. **P****referred Qualifications** * Professional certification or advanced training in AI architecture, applied generative AI, or enterprise AI system design. * Experience defining AI reference architectures, deployment patterns, and governance frameworks. * Familiarity with agentic workflows, retrieval systems, tool\-augmented AI, model orchestration, and agentic coding practices. * Experience in MLOps, AI observability, CI/CD, model governance, and lifecycle automation. * Strong understanding of prompt engineering, context engineering, retrieval design, and structured output management. * Experience with model benchmarking, red teaming, safety evaluations, and human\-in\-the\-loop review processes. * Ability to evaluate build\-vs\-buy options and select technologies based on architecture trade\-offs. * Experience authoring technical papers, patents, design standards, or architecture guidelines. * Strong mentoring and technical leadership experience. * Demonstrated experience driving teams through structured **spec\-driven development** and AI\-assisted engineering practices. **Key Competencies** * AI Architecture and Solution Design * Agentic Workflow Design * Retrieval\-Augmented and Tool\-Augmented Systems * Model and Prompt Evaluation Frameworks * Scalable Cloud AI Engineering * Data and Model Pipeline Engineering * MLOps and AI Observability * Security, Governance, and Responsible AI * Technical Leadership and Mentoring * Cross\-Functional Communication * Spec\-Driven Development Leadership * Agentic Coding Enablement **Role Impact** This role is ideal for a senior professional who operates as an AI architect and technical leader, capable of delivering high\-quality, governed, scalable AI systems. The successful candidate will not only build models but also define the architecture, evaluation, and operational framework that enables…