Leads applied AI research by translating ambiguous business problems into experiments, proof-of-concepts, and evaluated solution architectures. Develops and compares AI approaches involving machine learning, deep learning, generative AI, LLMs, RAG, and agentic AI. Creates implementation-ready engineering handoffs, reusable research assets, evaluation methods, and reference architectures while collaborating with business, product, engineering, data, cloud, and architecture teams. Mentors junior team members and provides hands-on technical leadership.
Lead Applied AI Research Engineer
Location: Hyderabad, India
Employment Type: Full-time
Work Model: On-site
Business Unit: Winfo Research Labs
Reporting To: Head of Winfo Research Labs
Role Type: Hands-on technical leadership and individual contributor role
Role Description
The Lead Applied AI Research Engineer will be WRL’s hands-on technical research leader responsible for converting complex and often ambiguous business problems into structured AI research and experimentation programs.
The role begins with understanding the business problem, breaking it into smaller decision and capability components, and determining which parts can be solved using established methods, which require experimentation, and which present genuine research opportunities. The Lead Applied AI Research Engineer will then formulate hypotheses, compare alternative approaches, build and evaluate proof-of-concepts, and determine whether a proposed solution has sufficient technical and business evidence to move into development.
This is not a purely academic research role, a conventional data science role, or a production engineering role. It is an applied research and technical leadership position for someone who can move comfortably between business problem discovery, AI research, experimentation, prototyping, evaluation, and solution architecture.
The successful candidate will work closely with business stakeholders, domain specialists, AI engineers, data engineers, cloud architects, product teams, and deployment specialists. Once an approach has been validated, the researcher will produce a clear engineering handoff covering the solution architecture, experimental evidence, evaluation results, data requirements, risks, constraints, and recommended implementation path.
Required Qualifications
- Demonstrated experience translating business or customer problems into applied AI solutions.
- Strong ability to break complex problems into researchable and executable components.
- Hands-on experience designing experiments and creating proof-of-concepts.
- Strong understanding of machine learning, deep learning, generative AI, LLMs, RAG, and agentic AI.
- Proficiency in Python and practical experience with modern ML and AI development frameworks.
- Experience defining evaluation criteria and comparing alternative models, architectures, or workflows.
- Ability to communicate technical findings, trade-offs, risks, and recommendations to both technical and non-technical audiences.
- Experience collaborating with software engineering, data, cloud, architecture, or product teams.
- Demonstrable portfolio of AI solutions, PoCs, prototypes, research projects, or shipped capabilities.
- Ability to work effectively in an ambiguous, rapidly evolving research and innovation environment.
Preferred Qualifications
- Master’s degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field.
- Experience with enterprise AI use cases and enterprise application environments.
- Understanding of cloud AI platforms, model serving, data pipelines, APIs, security, and observability.
- Experience developing reusable AI components, accelerators, or reference architectures.
- Experience with optimization, multimodal AI, knowledge graphs, fine-tuning, synthetic data, or advanced evaluation methods.
- Experience contributing to patents, publications, open-source projects, technical articles, or research communities.
- Previous experience in an applied research group, innovation lab, product organization, startup, or customer-facing technical role.
- Experience mentoring researchers, data scientists, or AI engineers.
A postgraduate research qualification is valuable but should not replace evidence that the candidate has previously converted a customer or business problem into a credible, evaluated solution. The WRL hiring material similarly lists a PhD as a bonus while emphasizing demonstrated AI solutions, research depth, technical literacy, and buildable specifications.
What Success Looks Like
A successful Lead Applied AI Research Engineer will:
- Turn ambiguous business opportunities into well-defined research and experimentation plans.
- Build PoCs that answer explicit feasibility and value questions.
- Use objective evaluation evidence to recommend whether an idea should proceed.
- Provide Development with clear, reproducible, and implementation-ready handoffs.
- Establish a repeatable applied research and PoC methodology for WRL.
- Create reusable knowledge, benchmarks, reference patterns, and technical assets.
- Help WRL avoid both premature production investment and endless experimentation.
- Build technical credibility with customers, internal stakeholders, researchers, and engineers.
- Develop junior team members while remaining directly involved in high-value technical work.
Similar Jobs
Artificial Intelligence • Cloud • Sales • Security • Software • Cybersecurity • Data Privacy
Operate and secure SailPoint’s global SaaS infrastructure. Responsibilities include file integrity monitoring, audit evidence automation, base-image hardening, release automation, vulnerability remediation, compliance support, incident response, and on-call production operations. The role collaborates with engineering and cybersecurity teams to securely deploy services, improve operational practices, troubleshoot systems and networks, and maintain security across AWS or Azure environments.
Top Skills:
AWSAzureChefIdsIpsJenkinsPuppetPythonRubySIEMSirpTerraformWaf
.jpeg)
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Defines end-to-end architectures for agentic AI, intelligent triage, and root-cause analysis platforms. Designs multi-agent systems, autonomous investigation workflows, human-in-the-loop controls, evaluation frameworks, and AI monitoring. Architects integrations across data, engineering, manufacturing, and AI platforms using APIs, microservices, and orchestration layers. Provides technical leadership, architectural governance, mentoring, and executive alignment while establishing standards for AI engineering, MLOps, and AgentOps.
Top Skills:
Agentic AiAgentopsAiopsAPIsAutogenAzure AiClaudeCloud-Native ArchitectureCrewaiDistributed SystemsGenerative AiGraphragKnowledge GraphsLangchainLanggraphLarge Language Models (Llms)MicroservicesMlopsNvidia AiOpenaiRag
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Defines enterprise data architecture for AI-driven triage and root-cause analysis systems. Designs data lakes, semantic layers, knowledge graphs, vector databases, schemas, ingestion pipelines, APIs, and governance frameworks. Establishes data quality, lineage, security, and observability standards across engineering and manufacturing domains. Enables GraphRAG, hybrid retrieval, agentic AI workflows, and low-latency inference at scale while partnering with cloud and infrastructure teams.
Top Skills:
Agentic AiAPIsArcadedbAWSAzureConfluenceData LakesData ModelingData WarehousesEtl/Elt PipelinesGoogle Cloud PlatformGraph DatabasesGraphragJIRAKnowledge GraphsLlm ApplicationsMetadata ManagementNeo4JRagTigergraphVector Databases
What you need to know about the Hyderabad Tech Scene
Because of its proximity to leading research institutions and a government committed to the city's growth, Hyderabad's tech scene is booming. With plans to establish India's first "AI city," the city is on track to become one of the world's most anticipated tech hubs, with companies like TransUnion, Schrödinger and Freshworks, among others, already calling the city home.
