SBI General Insurance Sales Executive

Supercharge Your Career as a Sr. Dev Engg at Technoidentity!

Are you ready to solve people challenges that fuel business growth? At Technoidentity, we’re a Data+AI product engineering company building cutting-edge solutions in the FinTech domain for over 13 years—and we’re expanding globally. It’s the perfect time to join our team of tech innovators and leave your mark!

What Will You Be Doing?

• Translate the designs into production grade implementation for the Invoice user flows.
• Understand how to integrate with apis's using graphql or any other async library etc.
• Work cross-functionally with product, design, and other engineering counterparts to clarify and implement the requirements.
• Drive, lead, and contribute to the full software development cycle: design, development, QA, experimentation, analysis, and launch.

What Makes You the Perfect Fit?

• 5+ years of full stack software development experience with strong expertise on front-end implementation.
• Experience with modern Javascript / TypeScript frameworks such as React, Preact, Angular, Next, Vue or Meteor.
• Hands-on experience writing, optimizing, and monitoring GraphQL queries and mutations in a production environment.
• Proficient in at least one major programming language (preferably Java / Kotlin).
• Exposure to architectural patterns of large, high-scale web applications, such as well-designed APIs, modular integrations and efficient algorithms.
• Passionate about design and building UX for customer facing applications.
• Outstanding communication and interpersonal skills with strong attention to detail.

Requirements

Front End First

• Solid hands on experience with React and TypeScript or an equivalent modern framework
• Ability to convert designs into clean, functional UI without hand holding
• Comfortable building and owning end to end user flows like forms, dashboards, and workflows
• Working knowledge of performance basics, accessibility, and responsive design

GraphQL

• Practical experience consuming GraphQL APIs
• Writing queries and mutations confidently
• Understanding how to handle loading, error states, and basic caching
• Does not need to design the entire schema, but should not treat GraphQL as magic either

Backend Awareness

• Working experience in Java or Kotlin
• Ability to understand existing backend services and make incremental changes
• Familiarity with APIs, data models, and basic system interactions
• Not expected to design large systems independently, but should ask the right questions

Engineering Hygiene  

• Writes readable, maintainable code
• Comfortable with unit tests and basic integration tests
• Experience working with code reviews and CI CD pipelines
• Understands production readiness and release discipline

Product and UX Sensibility

• Good eye for design and usability
• Can spot obvious UX gaps and raise them early
• Thinks in terms of user flows, not just tasks
• Understands trade offs between speed and quality

Collaboration Skills

• Can work well with PMs and Designers
• Communicates clearly and proactively
• Takes ownership of features, not just tickets
• Receptive to feedback and able to iterate fast.

JOB DETAILS:

* Job Title: Principal Data Scientist

* Industry: Healthcare

* Salary: Best in Industry

* Experience: 6-10 years

* Location: Bengaluru

Preferred Skills: Generative AI, NLP & ASR, Transformer Models, Cloud Deployment, MLOps

Criteria:

1. Candidate must have 7+ years of experience in ML, Generative AI, NLP, ASR, and LLMs (preferably healthcare).
2. Candidate must have strong Python skills with hands-on experience in PyTorch/TensorFlow and transformer model fine-tuning.
3. Candidate must have experience deploying scalable AI solutions on AWS/Azure/GCP with MLOps, Docker, and Kubernetes.
4. Candidate must have hands-on experience with LangChain, OpenAI APIs, vector databases, and RAG architectures.
5. Candidate must have experience integrating AI with EHR/EMR systems, ensuring HIPAA/HL7/FHIR compliance, and leading AI initiatives.

Job Description

Principal Data Scientist

(Healthcare AI | ASR | LLM | NLP | Cloud | Agentic AI)

Job Details

• Designation: Principal Data Scientist (Healthcare AI, ASR, LLM, NLP, Cloud, Agentic AI)
• Location: Hebbal Ring Road, Bengaluru
• Work Mode: Work from Office
• Shift: Day Shift
• Reporting To: SVP
• Compensation: Best in the industry (for suitable candidates)

Educational Qualifications

• Ph.D. or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field
• Technical certifications in AI/ML, NLP, or Cloud Computing are an added advantage

Experience Required

• 7+ years of experience solving real-world problems using:
• Natural Language Processing (NLP)
• Automatic Speech Recognition (ASR)
• Large Language Models (LLMs)
• Machine Learning (ML)
• Preferably within the healthcare domain
• Experience in Agentic AI, cloud deployments, and fine-tuning transformer-based models is highly desirable

Role Overview

This position is part of company, a healthcare division of Focus Group specializing in medical coding and scribing.

We are building a suite of AI-powered, state-of-the-art web and mobile solutions designed to:

• Reduce administrative burden in EMR data entry
• Improve provider satisfaction and productivity
• Enhance quality of care and patient outcomes

Our solutions combine cutting-edge AI technologies with live scribing services to streamline clinical workflows and strengthen clinical decision-making.

The Principal Data Scientist will lead the design, development, and deployment of cognitive AI solutions, including advanced speech and text analytics for healthcare applications. The role demands deep expertise in generative AI, classical ML, deep learning, cloud deployments, and agentic AI frameworks.

Key Responsibilities

AI Strategy & Solution Development

• Define and develop AI-driven solutions for speech recognition, text processing, and conversational AI
• Research and implement transformer-based models (Whisper, LLaMA, GPT, T5, BERT, etc.) for speech-to-text, medical summarization, and clinical documentation
• Develop and integrate Agentic AI frameworks enabling multi-agent collaboration
• Design scalable, reusable, and production-ready AI frameworks for speech and text analytics

Model Development & Optimization

• Fine-tune, train, and optimize large-scale NLP and ASR models
• Develop and optimize ML algorithms for speech, text, and structured healthcare data
• Conduct rigorous testing and validation to ensure high clinical accuracy and performance
• Continuously evaluate and enhance model efficiency and reliability

Cloud & MLOps Implementation

• Architect and deploy AI models on AWS, Azure, or GCP
• Deploy and manage models using containerization, Kubernetes, and serverless architectures
• Design and implement robust MLOps strategies for lifecycle management

Integration & Compliance

• Ensure compliance with healthcare standards such as HIPAA, HL7, and FHIR
• Integrate AI systems with EHR/EMR platforms
• Implement ethical AI practices, regulatory compliance, and bias mitigation techniques

Collaboration & Leadership

• Work closely with business analysts, healthcare professionals, software engineers, and ML engineers
• Implement LangChain, OpenAI APIs, vector databases (Pinecone, FAISS, Weaviate), and RAG architectures
• Mentor and lead junior data scientists and engineers
• Contribute to AI research, publications, patents, and long-term AI strategy

Required Skills & Competencies

• Expertise in Machine Learning, Deep Learning, and Generative AI
• Strong Python programming skills
• Hands-on experience with PyTorch and TensorFlow
• Experience fine-tuning transformer-based LLMs (GPT, BERT, T5, LLaMA, etc.)
• Familiarity with ASR models (Whisper, Canary, wav2vec, DeepSpeech)
• Experience with text embeddings and vector databases
• Proficiency in cloud platforms (AWS, Azure, GCP)
• Experience with LangChain, OpenAI APIs, and RAG architectures
• Knowledge of agentic AI frameworks and reinforcement learning
• Familiarity with Docker, Kubernetes, and MLOps best practices
• Understanding of FHIR, HL7, HIPAA, and healthcare system integrations
• Strong communication, collaboration, and mentoring skills

About the role:

Unico Connect is an Al-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies. We are hiring a Senior Al Engineer for a dedicated client engagement focused on building an Al-powered application builder platform - a product where users describe software in plain English and the system generates, previews, and iteratively refines working code. The mandatory requirement for this role is hands-on production experience shipping LLMpowered systems with agent architectures, with experience in code generation or developer tooling contexts a strong advantage. The role is product-focused and deeply hands-on. You will own everything between the user's prompt and correct code landing in the project: the agentic loop, code generation pipeline, context management, evaluation suite, and model cost strategy. You will work alongside the Senior MLOps Engineer who operationalises the infrastructure around your system, and collaborate closely with backend, frontend, and DevOps engineers.

Responsibilities:

Agent architecture: Design and own the agentic loop for the platform - request interpretation, planning, tool-calling sequence (read file, edit file, run build, search code, install package), and stop conditions. Make and revisit architectural decisions on singleagent vs. multi-agent designs, including planner/executor splits and dedicated buildrepair sub-agents.

Code generation pipeline: Own the end-to-end generation flow: task classification, context gathering, planning, targeted edits, verification, and commit. Implement diff/search-replace-based file editing with fuzzy matching and fallback strategies. Enforce scope discipline so the agent makes minimal diffs and does not modify code it was not asked to touch.

Self-repair loop: Build and tune the automated repair loop that pipes compiler, lint, build, and runtime errors back to the model with retry budgets and model escalation. This loop is the primary quality lever - the difference between 60-70% and 90%+ build success rates.

Context management: Build file-relevance retrieval so the agent sees the right files, not the whole codebase: dependency graphs, AST/tree-sitter-based chunking, embeddings, recency signals, and hybrid retrieval. Implement conversation summarisation and memory for long sessions, and address long-project degradation through codebase summaries and periodic consistency passes. Own token budgeting and prompt caching strategy.

Prompt engineering as a discipline: Own the system prompt and per-task prompt variants (new feature, bug fix, styling change). Maintain few-shot examples and enforce coding conventions, stack rules, and prohibited behaviours such as no hardcoded secrets and no whole-file rewrites. Version prompts like code with changelogs and rollback capability.

Evaluation and quality measurement: Design and own the evaluation suite: representative test prompts run on every prompt and model change, scored on build success rate, instruction adherence, and output quality including LLM-as-judge and visual/screenshot checks where relevant. Define regression gates that block qualitydegrading changes from shipping. Treat evals the way engineers treat automated testing: versioned, automated, and tracked over time. This responsibility is nonnegotiable at this level. 

Model strategy and cost: Design model routing - cheap and fast models for classification and small edits, frontier models for complex generation. Drive cost optimisation through prompt caching, diff-based edits over full-file rewrites, and tighter context selection. Track cost per agent run and tokens per task; evaluate new model releases against the eval suite and lead migrations when results justify it.

Safety and reliability of agent behaviour: Defend against prompt injection from user content and fetched web content. Ensure secrets never appear in generated client code. Define what the agent's tools may and may not do in collaboration with the platform team. Contribute to output moderation and abuse-pattern awareness.

Mentorship and engineering standards: Run code reviews, define engineering conventions for Al work, and raise the engineering bar across the Al team. Work closely with the Senior MLOps Engineer on handoff of eval design, prompt configurations, and model routing logic.

Requirements:

Hands-on production ownership of LLM-powered systems with agent architectures (mandatory). Must have personally shipped and operated at least one complex production Al system - agentic, multi-step, or code generation - with end-to-end ownership of architecture, evaluation, and cost. POCs, internal demos, and tutorialgrade work do not qualify.

5+ years of professional software or Al engineering experience, with at least 3 years focused on LLM applications, Al engineering, or production Al systems. Candidates with strong backend backgrounds and a clear, substantive pivot into LLM systems qualify.

Strong Python proficiency and service development. Production-grade Python with FastAPI or equivalent: type hints, async patterns, streaming responses, testing, and packaging. Not notebook-only. 

Depth across LLM APIs and agent systems. Production experience with at least two of OpenAl, Anthropic Claude, Google Gemini, or open-weight models (vLLM, Ollama, Together). Production experience with at least one agent framework (LangGraph, CrewAI, AutoGen, Llamalndex Agents) or hand-rolled equivalent. Hands-on with tool calling, structured outputs, and multi-step reasoning.

Demonstrated, systematic evaluation practice - non-negotiable. Must have built evaluation harnesses that gate production releases, not ad-hoc testing. Hands-on with at least one of LangSmith, Langfuse, Promptfoo, Ragas, or DeepEval. Candidates with no systematic answer to evaluation should not be considered at senior level regardless of other strengths.

Cost discipline for production Al. Track record of measurable cost optimisation on production Al features. Able to speak in specifics: cost per request, savings achieved through caching or model routing, context reduction decisions.

AWS working knowledge. Hands-on with EC2, S3, IAM, and Docker. Comfort with CI/CD workflows and deploying Al services.

Awareness of LLM security failure modes. Familiar with prompt injection patterns, understands that system prompt rules alone are insufficient, and has experience with output validation and content safety in production.

Nice to have: experience with AST/tree-sitter tooling, diff-based editing systems, or compiler-adjacent work; MCP server authoring; open-source Al contributions; published technical writing on LLM systems; multi-modal model experience; fine-tuning exposure (LORA, QLORA, PEFT).

Roles and Responsibilities:

As a Sales Executive, you will play a vital role in helping students achieve their goals by introducing them to our services and guiding them through the study-abroad process.

Client Acquisition:

• Identify and engage potential students interested in studying abroad, promoting its services to meet their educational needs.

Counselling and Consultation:

• Understand the academic goals and preferences of students.
• Explain suitable study packages, scholarship opportunities, and coaching options.

Sales and Enrollment:

• Promote and sell study-abroad packages to students and their families.
• Achieve monthly sales targets through effective engagement and follow ups.

Relationship Management:

• Build and maintain strong relationships with students and their families.
• Provide timely updates and assistance throughout the application process

.

Market Insights:

• Keep up to date with the latest trends in study-abroad programs and scholarships.
• Provide feedback on market demands to improve offerings.

Reporting and Coordination:

• Prepare and submit daily/weekly reports on sales and student inquiries.
• Collaborate with the operations and marketing teams to enhance sales strategies.

Qualifications: 

• Education: Bachelor's degree 
• Minimum 1.5 year of experience in sales
• Skills: - Excellent verbal and written communication in English. - Proficient in using MS Office (Excel, Word, PowerPoint). - Strong interpersonal and negotiation skills.
• Attributes: - Highly motivated and eager to learn. - Positive attitude with a customer-centric approach. - Ability to work independently and collaboratively.

Benefits:

• Competitive salary package with incentives.
• Incentive on every sale, Quarterly and Yearly Incentives. 
• Hands-on training and mentorship to develop sales and counselling skills.
• Opportunity to work with a dynamic team in a rapidly growing industry.
• Career growth opportunities within the organization.

Responsibilities

- To analysis business requirements, prepare design and implementation recommendations and estimate development effort

- Collaborate with cross-functional teams to define, design, and ship new features

- Lead or participate in design reviews, code reviews and architecture evolution discussions

- Unit-test code for robustness, including edge cases, usability, and general reliability

- Work on bug fixing and improving application performance

- Continuously discover, evaluate, and implement new technologies to maximize development efficiency

Required Skills

- Experienced with front-end programming language with React JS.

- Strong proficiency in JavaScript, including DOM manipulation and the JavaScript object model.

- Thorough understanding of React.js and its core principles.

- Experience with popular React.JS workflows (such as Flux or Redux)

-Experience on .Net Core

-Experience in database MS SQL

➢    Expert in React JS with about 4 years of experience

➢    Experience in using libraries like D3, Material UI, style sheets and theme management

➢    Should be able to understand requirements & design, develop efficient React JS Code, should have used tools to automate the test and deployment to production

➢    Should have good knowledge on REST APIs, Error handling and writing Unit and Integration Tests

➢    Knowledge of Java is desirable

Responsibilities

➢    Understand the Visual Designs, Functional Requirements and come up with the design/components needed to build the user interface.

➢    Work with Visual Designers to understand the graphic design patterns, themes, and implement in a structured way in the product front end

➢    Work with server side microservices team to develop the JSON contracts

➢    Develop efficient React JS code to implement these requirements

➢    Automate the testing and deployment of these components to production