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Lead AI Engineer Consultant
Lead AI engineering at Allstate India, designing agentic AI, semantic systems, and cloud data platforms. Set technical direction across products and strengthen production operations and engineering practices.
विवरण
- Share technical standards and reusable practices across business areas and technology stacks.
- Set cross-product technical direction with product managers, architects, engineers, and other stakeholders.
- Design product architecture that balances scale, security, resilience, performance, operations, cost, and delivery speed.
- Lead discovery, scoping, project inception, and iteration planning, turning product goals into system designs, technical backlogs, and delivery plans.
- Direct complex, business-critical engineering work across teams, products, sites, and platforms.
- Develop key components, validate designs, review code, and solve difficult technical problems.
- Design AI-enabled and data-intensive products using agentic AI, LLM services, semantic technologies, knowledge graphs, and data pipelines.
- Set up CI/CD, automated quality checks, secure engineering practices, and dependable release automation.
- Lead production readiness and operations, covering reliability, observability, security, performance, incident response, and product KPIs.
- Guide technology decisions, resolve team conflicts, and manage risks and dependencies across teams.
- Coach engineers in pair programming, test-driven development, secure coding, and knowledge sharing.
आवश्यकताएँ
- Bring at least 10 years of software engineering experience, including technical leadership on complex, production-grade products or platforms.
- Demonstrate expertise in software architecture, distributed and cloud-native design, hands-on development, automated testing, CI/CD, security, observability, and production operations.
- Program proficiently in Python and at least one other modern language.
- Show a track record of designing and delivering LLM-based and agentic AI systems, including model and agent evaluation, MLOps/LLMOps, AI observability, and responsible AI controls.
- Know semantic technologies such as RDF, OWL, enterprise ontologies, knowledge graphs, SPARQL, semantic alignment, and ontology mapping.
- Have experience with data engineering and analytics approaches, including ETL/ELT, lakehouse architecture, dimensional modelling, metadata-driven pipelines, and enterprise data models.
- Have delivered AI and data solutions on Microsoft Azure and Microsoft Fabric, or similar enterprise cloud platforms.
- Be able to lead architecture decisions across teams and products, mentor experienced engineers, establish standards, and influence product, engineering, data, security, and business stakeholders.
- Have owned production outcomes and used reliability, customer, and business KPIs to guide technical priorities and continuous improvement.
- A bachelor’s degree in Computer Science, Engineering, Data Science, or a related field is preferred.
- Equivalent education and relevant professional experience may be considered.
- Relevant certifications in cloud, data, architecture, or AI are preferred.
लाभ
- Develop skills and progress professionally.
- Challenge established practices and help shape the future of protection.
- Receive support for causes that matter to employees.
- Make a meaningful impact.
- Work in a hybrid arrangement.
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