Platform Engineering Lead

🚀 Job Title : Gen AI Engineer

Experience : 3 to 5 Years

Location : Bengaluru (MG Road – Prestige Building)

Work Mode : Hybrid (3 Days WFO)

Open Positions : 2

Notice Period : Immediate to 15–20 Days Preferred

🎯 Role Overview :

We are looking for a Gen AI Engineer with hands-on experience in building and deploying LLM powered applications.

You will work on cutting-edge AI solutions, including real-world enterprise use cases and next-generation internal products.

🛠 Mandatory Skills :

• Strong proficiency in Python.
• Hands-on experience with LLMs & GenAI frameworks (LangChain, LlamaIndex, Semantic Kernel).
• Experience in prompt engineering and system design.
• Knowledge of vector databases & embeddings.
• Experience integrating GenAI solutions into production systems.
• Understanding of REST APIs, async processing, and streaming responses.

⚡ AI / ML Knowledge :

• Strong understanding of NLP & transformer-based models.
• Familiarity with fine-tuning, embeddings, and inference patterns.
• Knowledge of GenAI evaluation metrics (accuracy, relevance, grounding).

☁ Infrastructure & Tooling :

• Experience with Cloud platforms (AWS / Azure / GCP).
• Familiarity with Docker & Kubernetes (good to have).
• Exposure to CI/CD pipelines and MLOps practices.

🌟 Nice to Have :

• Experience with multimodal models (vision, OCR, speech).
• Knowledge of AIOps, RCA, observability, enterprise workflows.
• Experience building AI agents & orchestration layers.
• Understanding of AI governance, safety, and responsible AI.

💼 Key Responsibilities :

• Design, develop, and deploy GenAI applications using LLMs (OpenAI, Azure OpenAI, open-source models).
• Build RAG pipelines using vector databases (FAISS, Pinecone, Weaviate, Chroma).
• Develop high-quality prompts, system instructions, and structured outputs (JSON, function calling).
• Integrate GenAI capabilities into backend systems via APIs & microservices.
• Optimize models for performance, latency, cost, and accuracy.
• Implement evaluation frameworks (hallucination detection, confidence scoring).
• Ensure data security, privacy, and compliance.
• Collaborate with product, design, and domain teams.
• Document architecture, prompts, and best practices.

💼🤝 Interview Process :

1. Geektrust Assessment (AI Agent-based evaluation)

2. Final Interview with Founder (45 mins)

Job Title: Chief Agentic Systems Architect

Location: Remote

Type: Contract

ROLE OVERVIEW

We are hiring a Chief Agentic Systems Architect to transform a 10+ year legacy codebase into a high‑velocity, agent‑operable architecture. This role sits at the intersection of software architecture, AI‑agent orchestration, and engineering governance. You will design system patterns, MCP interfaces, and cognitive context layers that allow LLMs and autonomous agents to safely refactor, test, and ship production code with minimal human intervention.

WHAT YOU’LL DO

1. AGENT‑OPERABLE SYSTEM ARCHITECTURE

• Decompose legacy monoliths into agent‑readable, modular systems with strict boundaries and single responsibility
• Lead incremental modernization using the Strangler Pattern, wrapping legacy logic in modern, contract‑driven interfaces
• Enforce SOLID principles, Dependency Injection, and Hexagonal Architecture to ensure deterministic AI execution and low regression risk

2. AGENTIC FRAMEWORK & MCP LEADERSHIP

• Architect and maintain the agent context layer: standardized Skills, Rules, and Commands for AI‑driven engineering workflows
• Build and operate Model Context Protocol (MCP) servers exposing legacy APIs, services, and databases as typed, secure, AI‑consumable tools
• Own contract‑first API design as the primary interface between human intent and autonomous agent execution

3. ENGINEERING GOVERNANCE & AI QUALITY CONTROL

• Act as architectural gatekeeper for AI‑generated pull requests, ensuring scalability, security, and long‑term maintainability
• Mandate test‑driven development (TDD) and characterization testing to preserve legacy behavior during refactoring
• Monitor and optimize agentic reasoning loops to balance cost, speed, and architectural integrity

WHAT WE’RE LOOKING FOR

• 6+ years in software architecture, platform engineering, or technical leadership
• Proven experience modernizing large, undocumented legacy systems
• Deep hands‑on expertise with TypeScript, .NET, and Node.js
• Strong background in API design, distributed systems, and modular architectures
• Practical experience with agentic development, MCP, LLM tooling, or AI‑assisted engineering
• Bias toward clean code, deterministic systems, and production‑grade AI

NICE TO HAVE

• Experience with remote‑first or globally distributed teams
• Background in SaaS transformations, scale‑ups, or private equity-backed environments
• Comfort operating in high‑ambiguity, high‑ownership settings

Role: Principal AI Architect — Multimodal Video Intelligence

Location: India Remote, with overlap with Singapore working hours

Employment Type: Full-time

Reporting to: Founder / CEO

Function: AI Architecture, Multimodal AI, Video Intelligence, Media Representation

About the Client

The client is building an AI-native media intelligence platform that transforms long-form video into structured, searchable, reusable and monetisable media intelligence.

The platform is not simply a video-clipping tool. We are developing a persistent intelligence layer for media, where video, audio, speech, text, objects, scenes, events, entities, emotions, narrative arcs and commercial signals are processed into a reusable representation that can support multiple downstream use cases, including:

• short-form clip generation;
• semantic search;
• scene and narrative understanding;
• contextual advertising;
• shoppable video;
• creator and content analytics;
• automated editing workflows;
• future media-intelligence APIs.

We are looking for a Principal AI Architect who can define and guide the AI architecture behind this platform.

Role Summary

The Principal AI Architect — Multimodal Video Intelligence will own the technical architecture for AI systems, including multimodal video understanding, persistent media representation, model orchestration, evaluation frameworks, and production AI design.

This is a hands-on architecture role. The ideal candidate can move between research papers, model selection, system design, data schemas, prototype review, engineering trade-offs, and implementation guidance.

You will work closely with the Founder / CEO, senior AI engineers, computer vision engineers, backend engineers and external vendors to convert the product and IP vision into a robust technical system.

Key Responsibilities

1. AI System Architecture

• Define the end-to-end AI architecture for long-form video understanding.
• Design the processing pipeline from video ingest to structured media intelligence.
• Define how vision, audio, speech, text, metadata and user signals should be fused.
• Design the architecture for reusable media intelligence rather than one-time clip generation.
• Ensure the system can support multiple downstream applications from the same processed media layer.

2. Persistent Media Representation

• Design persistent media representation layer across multiple levels, including frame, object, shot, scene, segment, entity, event and full-video levels.
• Define what intelligence must be stored permanently versus computed on demand.
• Design schemas for temporal, spatial, semantic, narrative and commercial metadata.
• Define provenance, confidence, model versioning and evidence-tracking requirements.
• Ensure the representation remains usable even when underlying AI models are replaced or upgraded.

3. Multimodal Model Strategy

• Select and evaluate appropriate models for video, image, audio, speech, OCR, entity extraction, scene understanding, action recognition, embeddings, reranking and LLM/VLM reasoning.
• Decide where to use open-source models, commercial APIs, fine-tuning or custom models.
• Define model interfaces so models can be swapped without breaking downstream systems.
• Guide model benchmarking for accuracy, latency, cost and scalability.
• Prevent over-dependence on any single model vendor or API.

4. Temporal and Narrative Intelligence

• Design approaches for understanding long-form video structure, including scenes, events, story arcs, character/entity continuity and engagement peaks.
• Define methods to identify clip-worthy moments across different content types.
• Support narrative scoring, highlight ranking, scene segmentation and coherence validation.
• Ensure that clips are not only visually interesting but contextually and narratively coherent.

5. Evaluation and Benchmarking

• Define objective evaluation frameworks for AI outputs.
• Build or guide creation of benchmark datasets and UAT criteria.
• Define metrics for clip quality, scene accuracy, entity continuity, timestamp alignment, hallucination control, ranking quality, retrieval precision and cost efficiency.
• Establish model and prompt evaluation processes.
• Create regression-testing methodology when models, prompts, schemas or scoring logic change.

6. Search, Retrieval and Knowledge Layer

• Design hybrid search architecture across transcript, visual events, metadata, embeddings and structured knowledge.
• Define when to use relational storage, vector databases, graph databases and object storage.
• Design queryable media intelligence for downstream APIs and applications.
• Support knowledge-graph or ontology-based representation where useful.
• Ensure retrieved outputs are evidence-backed and timestamp-grounded.

7. Production AI Architecture

• Work with AI engineers to convert architecture into deployable services.
• Guide decisions on batching, GPU inference, model serving, queues, retries, observability and cost controls.
• Review pipeline designs involving FFmpeg, GStreamer, DeepStream, TensorRT, Triton, ONNX, cloud services and model APIs.
• Define failure-handling, reprocessing, versioning and rollback mechanisms.
• Support scalable design without premature overengineering.

8. IP and Technical Differentiation

• Help translate AI architecture into defensible technical differentiation.
• Support patent-related technical disclosures where required.
• Identify what is proprietary versus commodity.
• Avoid building a generic wrapper over existing models.
• Ensure the architecture reinforces the core thesis of persistent, reusable media intelligence.

9. Team Guidance

• Provide technical direction to senior AI engineers and computer vision engineers.
• Review designs, experiments, evaluation results and architecture decisions.
• Mentor engineers without becoming a pure people manager.
• Help define technical milestones for the first 90, 180 and 365 days.
• Support hiring, technical interviews and vendor evaluation where needed.

Required Experience

The ideal candidate should have:

• 8+ years of AI/ML experience, with significant exposure to computer vision, video AI, multimodal AI, retrieval systems or production ML architecture.
• Strong experience designing AI systems, not only implementing isolated models.
• Hands-on experience with video understanding, temporal modelling, multimodal pipelines, VLMs, LLMs, embeddings, ranking or retrieval.
• Experience taking AI systems from prototype to production.
• Strong knowledge of Python and modern AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face or equivalent.
• Experience with model evaluation, benchmarking, error analysis and dataset design.
• Understanding of production architecture: APIs, queues, databases, cloud, model serving, observability and deployment trade-offs.
• Ability to work with founders and engineers in a high-ambiguity startup environment.

Strongly Preferred Experience

• Video understanding, action recognition, scene segmentation, event detection or video retrieval.
• Multimodal AI involving video, audio, speech, text and metadata.
• LLM/VLM orchestration for structured outputs.
• Prompt/version management, schema validation and hallucination control.
• Embedding search, vector databases, reranking and retrieval evaluation.
• Knowledge graphs, ontologies, entity resolution or temporal knowledge representation.
• Model serving using TensorRT, Triton, ONNX, vLLM, DeepStream or similar.
• Experience with long-form video, OTT, sports media, entertainment, creator platforms, advertising technology or social commerce.
• Experience contributing to patents, technical disclosures or investor diligence.

Technical Areas

The candidate should be comfortable discussing and making architecture decisions across:

• Computer vision;
• video AI;
• multimodal fusion;
• speech-to-text;
• OCR;
• image/video embeddings;
• VLMs and LLMs;
• semantic search;
• vector databases;
• graph databases;
• temporal reasoning;
• ranking and scoring systems;
• prompt orchestration;
• model evaluation;
• model versioning;
• data lineage;
• GPU inference;
• cloud AI deployment.

What This Role Is Not

This is not a role for someone who has only built:

• chatbots;
• basic RAG demos;
• LangChain prototypes;
• prompt-engineering workflows;
• simple OpenAI/Gemini API wrappers;
• dashboards over model outputs;
• classical computer vision demos without production architecture;
• MLOps pipelines without AI system-design depth.

The role requires architectural depth in AI systems, not just familiarity with AI tools.

First 90-Day Expectations

First 30 Days

• Review product thesis, patent direction, prototype plans and existing technical assumptions.
• Assess current team capability and architecture gaps.
• Define the first version of AI architecture.
• Identify immediate technical risks and validation priorities.

First 60 Days

• Deliver a detailed architecture document covering media representation, model stack, pipeline design, storage strategy, evaluation framework and implementation roadmap.
• Define the canonical media-intelligence schema.
• Define model-selection and benchmarking criteria.
• Guide senior engineers on first implementation milestones.

First 90 Days

• Help the team implement and validate the first working version of the persistent media-intelligence layer.
• Establish evaluation datasets and UAT metrics.
• Review prototype outputs and improve architecture based on evidence.
• Produce a 6-month AI roadmap with technical risks, milestones and resourcing needs.

Success Metrics

The Principal AI Architect will be successful if:

• They have a clear AI architecture that the engineering team can execute.
• The platform does not collapse into a generic clip-generation pipeline.
• The media representation is reusable across multiple use cases.
• Models, prompts and schemas are versioned and testable.
• AI outputs are measurable through objective benchmarks.
• Snehashish, Abhishek and other engineers have clear technical direction.
• The architecture supports both product execution and investor/IP defensibility.

Candidate Personality Fit

The right candidate should be:

• intellectually strong but practical;
• hands-on enough to review code and experiments;
• comfortable with ambiguity;
• willing to challenge assumptions with evidence;
• able to simplify complex AI architecture for engineers and investors;
• disciplined about evaluation, cost and production constraints;
• not attached to one model, tool or vendor;
• able to work in a founder-led early-stage startup. 

An Associate Professor is a mid-to-senior academic position in colleges and universities, typically above Assistant Professor and below Professor.

Joining:Immiate Joining

Qualifications:

In many institutions, especially in India:

• Ph.D. in a relevant discipline
• Teaching/research experience (often 8+ years)
• Research publications in indexed journals
• API score/research contributions as per institutional norms
• Eligibility criteria based on UGC or AICTE guidelines

Skills Required:

• Subject expertise in the specialization area
• Research and publication skills
• Classroom and laboratory management
• Communication and mentoring
• Leadership and academic coordination
• Technical and industry-oriented knowledge

Main Responsibilities:

• Teaching undergraduate and postgraduate students
• Conducting research and publishing papers
• Guiding student projects, internships, and theses
• Developing curriculum and course materials
• Participating in academic administration
• Applying for research grants and patents
• Mentoring junior faculty and students
• Contributing to accreditation activities such as NBA/NAAC

Technical / Domain Skills:

• Programming languages: Java, Python, C, C++, JavaScript
• Database systems: SQL, NoSQL, data modeling
• Software engineering and system design
• Artificial Intelligence & Machine Learning
• Data Science & Big Data Analytics
• Cloud Computing (AWS, Azure, Google Cloud)
• Cybersecurity and Network Security

Research Skills:

• Research methodology and experimental design
• Publishing in SCI/Scopus journals
• Writing research proposals and grant applications
• Patent filing and innovation development
• Data analysis and statistical tools
• Literature review and technical documentation
• Conference presentation and paper reviewing

Career Progression:

Assistant Professor → Associate Professor → Professor → Dean/HOD/Research Director

In conclusion, an Associate Professor plays a vital role in higher education by balancing teaching, research, student mentoring, and academic leadership. The position requires strong subject expertise, continuous learning, research contributions, and effective communication skills. Associate Professors contribute significantly to institutional growth, innovation, and the overall development of students and academic programs.

Job Title: State Sales head Job Category: Full time

Qualification Graduate in computer science, BE, /MBA Location Haryana State

Salary Range 50000 PM + Incentives Experience: More than 5 years

Position Overview: We are seeking a State Sales head with a passion for education and a proven track record

in sales to lead and expand our presence in the Haryana state. Ambitious and energetic candidates required

expertise in customer acquisition strategy & dedication for effective sales & marketing strategy to drive

sustainable financial growth with forging strong relationships & product knowledge.

Key Responsibilities:

● Sales Strategy: Develop & execute a comprehensive sales strategy that aligns with the company's

goals and objectives. Continuously evaluate and refine the strategy based on market trends & customer

feedback.

● Revenue Growth: Meet and exceed revenue targets by identifying business opportunities, negotiating

contracts, and managing the sales pipeline. Foster long-term relationships with key accounts.

● Market Analysis: Stay updated on industry trends, customer needs to inform product development and

sales strategies. Conduct market research, competition & competitor analysis to identify opportunities

for growth.

● Sales Process Optimization: Implement & improve sales processes, systems & follows the best

practices in sales and customer relationship management, use tools to enhance efficiency &

effectiveness.

● Reporting and Analysis: Regularly analyze sales data and performance metrics to provide insights

and recommendations for improvement. Present reports to senior management to track progress and

make informed decisions.

● Customer Engagement: Collaborate with the marketing team to create targeted marketing campaigns,

promotions, and events to attract and retain customers. Ensure exceptional customer satisfaction

through effective communication and support.

● Collaboration: Identify and establish strategic partnerships with educational institutions, organizations

& other stakeholders to expand the company's reach and influence in the EdTech sector.

Qualification and experience:

● Proven working experience as a State Sales head in K-12 or CBSE school business,

● Proven sales track record, computer Proficiency for proposal development & CRM tools

● Market knowledge, strong relationship is expected with ability to build rapport

● Good analytical & Strong problem solving skills, listening and questioning skills, combined with the

ability to interact confidently with clients, able to work under pressure in result oriented manner

● Graduate from any branch computer science, MBA, BA, B.Com

● Edtech/Book publisher or sales & marketing experience are added advantages

Company Profile: Scholarclone is an innovative EdTech company committed to transforming education

through cutting-edge technology solutions. We provide a range of online learning & administrative platforms,

resources, & tools designed to empower educators and learners alike. With a mission to make education

accessible and engaging, administrative solutions and integrated business applications to a wide spectrum of

clients including education institutes.

• 3+ year of experience in Development in JAVA technology.
• Strong Java Basics
• SpringBoot or Spring MVC
• Experience in AWS.
• Hands on experience on Relationl Databases (SQL query or Hibernate) + Mongo (JSON parsing)
• Proficient in REST API development
• Messaging Queue (RabitMQ or Kafka)
• Microservices
• Any Caching Mechanism
• Good at problem solving

Good to Have Skills:

• 3+ years of experience in using Java/J2EE tech stacks
• Good understanding of data structures and algorithms.
• Excellent analytical and problem solving skills.
• Ability to work in a fast paced internet start-up environment.
• Experience in technical mentorship/coaching is highly desirable.
• Understanding of AI/ML algorithms is a plus.
• 2.5+ year of experience in Development in JAVA technology.
• Strong Java Basics
• SpringBoot or Spring MVC
• Experience in AWS.
• Hands on experience on Relationl Databases (SQL query or Hibernate) + Mongo (JSON parsing)
• Proficient in REST API development
• Messaging Queue (RabitMQ or Kafka)
• Microservices
• Any Caching Mechanism
• Good at problem solving

Responsibilities:

• Design, configure, administer, monitor and troubleshoot complex enterprise network environment for communications and solution improvements within the Company's high-traffic, business-critical Internet production environment. 
• Develop and implement plans for infrastructure upgrades, modeling, analysis, and planning.
• Analyze, design, test, and evaluate network systems including local area networks (LAN), wide area networks (SD-WAN), Cloud, Data Centers, and other data communications systems. 
• Design, manage, and maintain office wired and wireless networks.
• Work with complex network and storage environments including SAN, clustering, load balancing, multi-site VPNs, network IDS, and firewalls.
• Monitor network performance and provide security measures, troubleshooting and maintenance, as needed. 
• Acquire, maintain and report on data related to network performance management, capacity planning and utilization trend analysis.
• Provide after-hours support for systems and applications.
• Collaborate with other functional IT areas to ensure that IT best practices, policies, and procedures are adhered to. Provide technical support for staff issues.
• 7+ years of experience in setup, configuration and maintenance of networking infrastructure including Cisco switches, routers, firewalls, VPN technologies, SD-WAN, and other WAN administration.

Experience

• 7+ years of experience with configuring and supporting IP networks.
• 5+ years of experience with Google Cloud Platform (GCP) and multi-region Amazon Web Services (AWS) networking configurations
• 3+ years of experience in managing Meraki wireless networks and equipment in office environments.
• Strong fundamental knowledge of networks, ports, protocols, and infrastructure setup
• Enterprise-Level: Larger than 1,000 PCs and 500 Servers (multi-platform) are a definite plus
• Solid understanding of Microsoft Active Directory, DNS, DHCP, etc. in a large multi-site environment.
• In-depth knowledge of IT standards, concepts, best practices, and procedures - relies on knowledge, experience and judgment to plan and accomplish goals.
• Excellent verbal and written communication skills for purposes of communicating with team members as well as other departments.
• Ability to take initiative & manage multiple detailed tasks in a fast-paced and ever-changing environment.
• Organizational, and project management abilities, strong analytical and problem-solving skills

Education Qualifications:

• Bachelor's Degree: CIS Computer Information Systems; Information Technology, Computer Science or similar.
• CCNP Certification or similar
• Cisco switches, routers, firewalls, VPN technologies, SD-WAN, WAN administration
• Cisco SAN experience
• OS Platforms: Windows / Linux
• Hardware Platforms: Cisco UCS, Cisco Meraki, EMC storage

1. Developing HMI application in Qt or similar UI frameworks
2. Develop C++ or Rust backends for the HMI
3. Understand and optimize potential performance bottlenecks