3+ Knowledge base Jobs in India

JOB TITLE AND SUMMARY:

Job Title: Lead I — Software Engineering - AI Solutions Analyst

Location: Bangalore, India 

Experience: 6–8 Years 

Openings: 1 

Salary: Best in Industry 

Notice Period: Immediate–30 Days

ROLE SUMMARY: 

Lead the design and operationalization of LLM-driven business intelligence solutions by bridging data engineering, BI, and AI application teams. Own context/knowledge design, prompt engineering, evals, and governance inputs to ensure GPT-based outputs are accurate, compliant, and business-aligned.

CORE RESPONSIBILITIES:

• Define LLM interaction architecture: context injection, retrieval logic, prompt templates, orchestration flows.
• Design and curate knowledge base: taxonomy, canonical definitions, metadata and access labels.
• Lead prompt engineering: intent mapping, template library, temperature/top-p guidance, and fallback strategies.
• Implement and run evaluation pipelines: create labeled eval sets, scoring rubrics, automated/manual tests, and baseline reporting.
• Collaborate with Data Analysts and SMEs to map, tag, and validate dataset semantics and lineage.
• Ensure governance and compliance: data redaction, access controls, logging, bias checks, and secure deployment patterns.
• Monitor production performance: telemetry, hallucination tracking, user feedback loop, and iterative prompt/KB improvements.
• Produce documentation and training material: playbooks, runbooks, onboarding guides, and stakeholder reports.

KEY DELIVERABLES:

• LLM Interaction Design Framework: architecture, context windows, retrieval strategy, and orchestration flows.
• Knowledge Base Configuration: taxonomy, concept mappings, canonical definitions, update process, and access labels.
• Prompt Library and Usage Guidelines: categorized templates, examples, failure modes, and parameter recommendations.
• Evaluation Scripts and Test Results: labeled eval sets, scoring criteria, automated scripts (SQL/Python), and baseline reports.
• AI Performance Dashboard: metrics for accuracy, hallucination rate, intent coverage, latency, and business-impact KPIs.
• Governance Package: data-security controls, bias mitigation checklist, incident runbook, and compliance inputs.

REQUIRED SKILLS AND TOOLS:

• Core Competencies: LLM integration, prompt engineering, context and KB design, evaluation methodology.
• Technical Skills: SQL; Python for ETL, eval automation, and scripting; familiarity with Databricks and AWS services.
• Platform Experience: ChatGPT-style APIs or equivalent, RAG architectures, vector stores, and retrieval tooling.
• Evaluation Expertise: designing eval datasets, scoring rubrics, A/B testing, and automated pipelines.
• Governance Knowledge: data redaction, access controls, privacy-preserving techniques, and bias checks.
• Soft Skills: cross-functional collaboration, stakeholder alignment, technical writing, and change management.

NICE TO HAVE SKILLS:

Data Literacy & Modelling Awareness Familiarity with Databricks, AWS, and ChatGPT Environments.

ACTIONABLE INFORMATION: INTERVIEW DRIVE:

DATES: 23, 24, 27, 28, 29, 30 October 2025

FORMAT: Virtual or on-site panels as scheduled; candidates must be available for rounds within these dates.

ROUNDS: 3–4 (Technical screen, Practical task / take-home, Deep technical panel, Stakeholder / Behavioral + Offer discussion).

INTERVIEW FOCUS AREAS AND SAMPLE QUESTIONS:

• LLM Integration and RAG Design:
• Explain a RAG pipeline for joining relational sales KPIs with unstructured product notes.
• How do you choose chunk size and retriever configuration for time-series sales data?
• Prompt Engineering and Failure Handling:
• Provide three prompt templates for a sales-analytics assistant and describe failure/fallback logic.
• How do you control verbosity and factuality in LLM responses for regulatory contexts?
• Evaluation and Metrics:
• Design a 10–20 query eval set for revenue-forecasting answers and a scoring rubric.
• Which metrics would you instrument to detect increasing hallucination trends?
• Data and Governance:
• Describe how you would tag and redact PII before feeding context to an LLM.
• How would you align disparate stakeholder definitions of "closed deal" across systems?

CANDIDATE EVALUATION RUBRIC:

• Technical LLM Knowledge: understanding of RAG, context windows, hallucination mitigation.
• Prompt Engineering Ability: clarity, robustness, failure handling, reusability.
• Data & Integration Skills: SQL/Python competence, mapping data to business concepts, lineage awareness.
• Evals & Metrics Rigor: quality of eval sets, scoring criteria, automation approach.
• Governance & Security Awareness: practical controls for privacy, access, bias mitigation and compliance readiness.
• Communication & Collaboration: ability to document, present, and align stakeholders.

It is an all-in-one e-commerce logistics platform using modern software to provide

fast and affordable fulfillment. Brands of all sizes use our full-service solution to

store inventory at warehouses near their customers and ship orders with the company carrier

network to improve transit times and shipping costs. Our deep integration with sales

channels enables brands to earn prime-like badges to accelerate their sales.

We are looking forward to onboard a committed Technical Writer who is motivated enough

to combine his analytical, communication and managerial skills in order to administer our

support and customers in the best possible manner.

Managing a team of support agents, providing training, monitoring, and mentoring as needed.

Developing and implementing policies and procedures related to support operations.

Collaborating with other members of different departments to identify and resolve escalated

issues.

Ensuring that support agents have the necessary tools and resources to do their jobs effectively.

Maintaining and reporting on key performance indicators (KPIs) related to support operations.

Developing and delivering training programs to improve the skills of the support team.

Continuously review and analyze business processes to identify areas of improvement and

develop strategies to enhance support performance.

Identifying and implementing process improvements to increase efficiency and customer

satisfaction.

Identifying and documenting business processes

Writing documents like help articles, SOPs, and other materials that explain complex technical

concepts in an easy-to-understand way.

Work with the subject matter experts to gather information about the products or processes

that they are documenting.

Editing and revising documents that have already been written by other team members or

subject matter experts to ensure accuracy and consistency.

Work closely with other teams to gather information, review documentation, and ensure that

the documentation meets the needs of the audience.

Managing the entire documentation process, from planning and research to writing and

publishing.

Responsible for ensuring that documentation is up-to-date and easily accessible to end-users.

Very good verbal and written communication

Good knowledge of grammar and sentence formation

Engineering background shall be preferred

Any prior experience in a similar role or in any e-commerce fulfillment domain/ return related

operations would be a plus point

It is an amalgamation of enthusiastic and genius people working on a remarkable

concept, making headway in this industry. It would not only provide you a scope for

professional and personal growth but would also provide you a lot of avenues to experiment

with and expertise in your skills.