Applied AI Lead

Inflect is a policy intelligence and systems-diagnostics firm working at the intersection of public policy, regulatory foresight, and institutional reform. We partner with governments, multilaterals, and private-sector stakeholders to diagnose systemic delivery failures, map policy architecture, and design implementation-ready interventions across sectors, including climate resilience, public health, fiscal systems, digital governance, land administration, EV policy, and social protection.

Our work is deeply research-driven, politically informed, and implementation-focused. We are building a team that combines analytical rigour with strong stakeholder engagement and the ability to translate complex policy insight into actionable partnerships.

The Applied AI Lead will build and deploy sophisticated AI models tailored to public policy challenges, such as impact evaluation or predictive analytics for socioeconomic programs. They adapt research analyst skills like data analysis to AI engineering, focusing on policy-relevant applications.

Beyond their analytical output, this person will be a senior point of reference within the team. Colleagues working on technical implementations from AI-based data extraction to geospatial analysis and ML classification of government schemes will rely on them to provide policy grounding, validate research outputs, and ensure that the firm's technology-driven work is anchored in genuine policy understanding.

To deliver high-quality, senior-level technical expertise that drives Inflect's product and engineering initiatives, while serving as the most experienced technical voice in the room- the person the team turns to when they need to understand how a tech-based system should be engineered, how different components integrate within a larger technical ecosystem, or how design intent translates into scalable, reliable, and production-ready solutions.

A. Core Responsibilities

• Lead the design, development, and deployment of advanced end-to-end AI/ML models across priority domains, including data ingestion frameworks, ETL pipelines, model pipelines, and deployment infrastructure.
• Develop and operationalise high-impact use cases, including predictive modelling, NLP-based classification systems, and generative AI applications for policy intelligence.
• Ensure all models meet standards of scalability, interpretability, and production readiness.
• Integrate diverse data sources, including government repositories (eGazette, parliamentary APIs, ministry datasets, PIB), ensuring robustness and interoperability.
• Establish and enforce protocols for data quality, version control, and reproducibility.
• Define and implement rigorous frameworks for model evaluation, validation, and performance monitoring.
• Proactively monitor and address model drift, data inconsistencies, and system performance risks.
• Lead the translation of AI outputs into deployable products, including dashboards, APIs, and decision-support tools.

B. Supporting Responsibilities

• Contribute to maintaining shared repositories of datasets, models, codebases, and agent configurations.
• Enable reuse, documentation, and version control across teams.
• Collaborate with engineers and analysts to refine feature engineering, training schemas, and fine-tuning strategies.

Essential Experience

• Proven expertise in AI model development for domain-specific use cases, including panel data handling, time-series forecasting, and generative AI for policy drafting or summarisation.
• Experience deploying AI agents (e.g., autonomous agents using frameworks like LangChain, AutoGen, or CrewAI) for policy workflows, such as multi-step reasoning for scenario analysis, real-time data synthesis from government reports, or agentic simulations of economic interventions.
• Strong programming in Python/R/Stata with ML libraries; experience deploying models ethically in regulated environments like government data (bias mitigation, privacy compliance).
• Experience with API development, system integration, and database management (SQL/NoSQL).
• Familiarity with cloud platforms and modern development practices, including version control and CI/CD.

Skills & Attributes

• Intellectual confidence to serve as a senior reference point, comfortable fielding domain questions from technically capable colleagues and providing grounded, well-reasoned answers.
• Organised, thorough, and capable of managing multiple research workstreams simultaneously without compromising quality.

Preferred Background

• Extensive exposure to AI-assisted research workflows, NLP-based classification systems, automated data pipelines, and building AI for public sector applications (e.g., urban planning trends, climate forecasting, or government accounting errors).
• Experience working on development policy issues is preferred.
• Familiarity with geospatial or environmental data in a policy and agricultural context is an added advantage.

• Technology-assisted research that is grounded in accurate policy understanding because this person has reviewed it and ensured it reflects how government actually works.
• A structured, living knowledge base of codes, AI-driven tools and systems, policy sources and scheme classifications that becomes a durable institutional asset.
• A team that operates with greater policy confidence because a senior expert is in the room who has seen these systems from the inside.

• Work at the frontier of policy intelligence and technology where AI-assisted research meets real government decision-making.
• Operate in an intellectually rigorous environment that treats policy analysis as a discipline, not a support function.
• Engage with complex, consequential policy challenges across India's most important governance domains.
• Be part of building a firm that combines analytical depth with institutional trust and a genuine commitment to policy impact.

If you are excited by the prospect of applying your that expertise in a technology-forward, analytically rigorous setting, we would like to hear from you.

Please share your CV along with a short note describing your experience in policy research and any exposure to data-driven or AI-assisted research workflows. You can reach us at [Confidential Information]