Pricing Manager

The requirements are as follows:

1) Familiar with the the Django REST API Framework.

2) Experience with the FAST API framework will be a plus

3) Strong grasp of basic python programming concepts ( We do ask a lot of questions on this on our interviews :) )

4) Experience with databases like MongoDB , Postgres , Elasticsearch , REDIS will be a plus

5) Experience with any ML library will be a plus.

6) Familiarity with using git , writing unit test cases for all code written and CI/CD concepts will be a plus as well.

7) Familiar with basic code patterns like MVC.

8) Grasp on basic data structures.

You can contact me on nine three one six one two zero one three two

Job Details

- Job Title: Enterprise Sales Manager (B2B SaaS)

- Industry: Software Technology Company

- Experience Required: 2-10 years

- Working Days: 5 days/week

- Job Location: Mumbai

- CTC Range: Best in Industry

Review Criteria

• Strong enterprise sales executive profile
• 2+ years of selling B2B SaaS.
• Must have 2+ of experience of selling to enterprise clients OR to manufacturing industry OR selling FinTech product, SAP Product sales/Finance ERP solutions (like invoice processing, vendor management, Source to pay, Compliance solutions).
• Must have experience in end-to-end sales from lead generation, prospecting, demos, proposal building, negotiation, and deal closure
• Must have stable career history — no frequent job hopping
• Final round is F2F (client will handle the travel)

Role & Responsibilities

We are looking for a dynamic and results-driven Enterprise Sales Manager to drive our sales strategy and expand our market presence. This role demands a strong understanding of SAP/Finance ERP solutions, excellent communication skills, and a proven track record in IT/software sales.

Key Responsibilities:

• Sales Strategy Development: Develop and execute sales plans to achieve company revenue targets in the SAP/ERP domain.
• Client Acquisition: Identify, engage, and convert prospective clients by demonstrating the value of our SAP/ERP solutions.
• Relationship Management: Build and maintain long-term relationships with clients, ensuring high levels of satisfaction and retention.
• Market Analysis: Stay updated on industry trends, competitor activities, and market demands to identify growth opportunities.
• Proposal & Presentation: Prepare and deliver compelling proposals, presentations, and demos tailored to client needs.
• Collaboration: Work closely with technical and consulting teams to ensure seamless delivery of solutions and services.

Ideal Candidate

• Experience: Minimum 2 years in sales, with a strong focus on SAP Product sales/Finance ERP solutions
• Industry Preference: Candidates with prior experience in handling manufacturing industry clients will be given preference.
• Educational Qualification: Bachelor’s degree in Business, IT, or a related field. An MBA is an added advantage.

Skills:

• Proven ability to meet and exceed sales targets.
• Excellent communication, negotiation, and presentation skills.
• Understanding of SAP/ERP systems and their applications in business processes.
• Strong client relationship management abilities.
• Track record of success managing large enterprise accounts
• Track record of consistently over-achieving quota (top 10% in your company)
• Strong interpersonal and presentation skills
• Exceptional verbal and written communication skills
• Ability to travel to prospects and customers if required
• Good organizer with the ability to prioritize and multitask
• Proven ability to manage multiple concurrent sales cycles.

SENIOR DATA ENGINEER:

ROLE SUMMARY:

Own the design and delivery of petabyte-scale data platforms and pipelines across AWS and modern Lakehouse stacks. You’ll architect, code, test, optimize, and operate ingestion, transformation, storage, and serving layers. This role requires autonomy, strong engineering judgment, and partnership with project managers, infrastructure teams, testers, and customer architects to land secure, cost-efficient, and high-performing solutions.

RESPONSIBILITIES:

• Architecture and design: Create HLD/LLD/SAD, source–target mappings, data contracts, and optimal designs aligned to requirements.
• Pipeline development: Build and test robust ETL/ELT for batch, micro-batch, and streaming across RDBMS, flat files, APIs, and event sources.
• Performance and cost tuning: Profile and optimize jobs, right-size infrastructure, and model license/compute/storage costs.
• Data modeling and storage: Design schemas and SCD strategies; manage relational, NoSQL, data lakes, Delta Lakes, and Lakehouse tables.
• DevOps and release: Establish coding standards, templates, CI/CD, configuration management, and monitored release processes.
• Quality and reliability: Define DQ rules and lineage; implement SLA tracking, failure detection, RCA, and proactive defect mitigation.
• Security and governance: Enforce IAM best practices, retention, audit/compliance; implement PII detection and masking.
• Orchestration: Schedule and govern pipelines with Airflow and serverless event-driven patterns.
• Stakeholder collaboration: Clarify requirements, present design options, conduct demos, and finalize architectures with customer teams.
• Leadership: Mentor engineers, set FAST goals, drive upskilling and certifications, and support module delivery and sprint planning.

REQUIRED QUALIFICATIONS:

• Experience: 15+ years designing distributed systems at petabyte scale; 10+ years building data lakes and multi-source ingestion.
•  Cloud (AWS): IAM, VPC, EC2, EKS/ECS, S3, RDS, DMS, Lambda, CloudWatch, CloudFormation, CloudTrail.
• Programming: Python (preferred), PySpark, SQL for analytics, window functions, and performance tuning.
• ETL tools: AWS Glue, Informatica, Databricks, GCP DataProc; orchestration with Airflow.
• Lakehouse/warehousing: Snowflake, BigQuery, Delta Lake/Lakehouse; schema design, partitioning, clustering, performance optimization.
• DevOps/IaC: Terraform with 15+ years of practice; CI/CD (GitHub Actions, Jenkins) with 10+ years; config governance and release management.
• Serverless and events: Design event-driven distributed systems on AWS.
• NoSQL: 2–3 years with DocumentDB including data modeling and performance considerations.
• AI services: AWS Entity Resolution, AWS Comprehend; run custom LLMs on Amazon SageMaker; use LLMs for PII classification.

NICE-TO-HAVE QUALIFICATIONS:

• Data governance automation: 10+ years defining audit, compliance, retention standards and automating governance workflows.
• Table and file formats: Apache Parquet; Apache Iceberg as analytical table format.
• Advanced LLM workflows: RAG and agentic patterns over proprietary data; re-ranking with index/vector store results.
• Multi-cloud exposure: Azure ADF/ADLS, GCP Dataflow/DataProc; FinOps practices for cross-cloud cost control.

OUTCOMES AND MEASURES:

• Engineering excellence: Adherence to processes, standards, and SLAs; reduced defects and non-compliance; fewer recurring issues.
• Efficiency: Faster run times and lower resource consumption with documented cost models and performance baselines.
• Operational reliability: Faster detection, response, and resolution of failures; quick turnaround on production bugs; strong release success.
• Data quality and security: High DQ pass rates, robust lineage, minimal security incidents, and audit readiness.
• Team and customer impact: On-time milestones, clear communication, effective demos, improved satisfaction, and completed certifications/training.

LOCATION AND SCHEDULE:

●      Location: Outside US (OUS).

●      Schedule: Minimum 6 hours of overlap with US time zones.

We are seeking an experienced AI Architect to design, build, and scale production-ready AI voice conversation agents deployed locally (on-prem / edge / private cloud) and optimized for GPU-accelerated, high-throughput environments.

You will own the end-to-end architecture of real-time voice systems, including speech recognition, LLM orchestration, dialog management, speech synthesis, and low-latency streaming pipelines—designed for reliability, scalability, and cost efficiency.

This role is highly hands-on and strategic, bridging research, engineering, and production infrastructure.

Key Responsibilities

Architecture & System Design

• Design low-latency, real-time voice agent architectures for local/on-prem deployment
• Define scalable architectures for ASR → LLM → TTS pipelines
• Optimize systems for GPU utilization, concurrency, and throughput
• Architect fault-tolerant, production-grade voice systems (HA, monitoring, recovery)

Voice & Conversational AI

• Design and integrate:
• Automatic Speech Recognition (ASR)
• Natural Language Understanding / LLMs
• Dialogue management & conversation state
• Text-to-Speech (TTS)
• Build streaming voice pipelines with sub-second response times
• Enable multi-turn, interruptible, natural conversations

Model & Inference Engineering

• Deploy and optimize local LLMs and speech models (quantization, batching, caching)
• Select and fine-tune open-source models for voice use cases
• Implement efficient inference using TensorRT, ONNX, CUDA, vLLM, Triton, or similar

Infrastructure & Production

• Design GPU-based inference clusters (bare metal or Kubernetes)
• Implement autoscaling, load balancing, and GPU scheduling
• Establish monitoring, logging, and performance metrics for voice agents
• Ensure security, privacy, and data isolation for local deployments

Leadership & Collaboration

• Set architectural standards and best practices
• Mentor ML and platform engineers
• Collaborate with product, infra, and applied research teams
• Drive decisions from prototype → production → scale

Required Qualifications

Technical Skills

• 7+ years in software / ML systems engineering
• 3+ years designing production AI systems
• Strong experience with real-time voice or conversational AI systems
• Deep understanding of LLMs, ASR, and TTS pipelines
• Hands-on experience with GPU inference optimization
• Strong Python and/or C++ background
• Experience with Linux, Docker, Kubernetes

AI & ML Expertise

• Experience deploying open-source LLMs locally
• Knowledge of model optimization:
• Quantization
• Batching
• Streaming inference
• Familiarity with voice models (e.g., Whisper-like ASR, neural TTS)

Systems & Scaling

• Experience with high-QPS, low-latency systems
• Knowledge of distributed systems and microservices
• Understanding of edge or on-prem AI deployments

Preferred Qualifications

• Experience building AI voice agents or call automation systems
• Background in speech processing or audio ML
• Experience with telephony, WebRTC, SIP, or streaming audio
• Familiarity with Triton Inference Server / vLLM
• Prior experience as Tech Lead or Principal Engineer

What We Offer

• Opportunity to architect state-of-the-art AI voice systems
• Work on real-world, high-scale production deployments
• Competitive compensation and equity (if applicable)
• High ownership and technical influence
• Collaboration with top-tier AI and infrastructure talent

1. Senior Oracle Consultant: Oracle EBS + Fusion+ OCI | 10+ Yrs | Standard IST
2. Oracle ERP | 7+ Yrs | Standard IST

• Experience on Angular 7+
• Experience of SCSS, Type script
• Knowledge of API integration
• Experience of npm package repository
• Experience of Git
• Experience of html, CSS, JS, JQuery and BootStrap

Note:- Angular developer with any combination will do for eg- Angular Dev with PHP, Angular Dev with Java or dotnet will also do. They should have worked on Angular 6 or any version above that

Key Roles/Responsibilities: –

• Develop an understanding of business obstacles, create

• solutions based on advanced analytics and draw implications for

• model development

• Combine, explore and draw insights from data. Often large and

• complex data assets from different parts of the business.

• Design and build explorative, predictive- or prescriptive

• models, utilizing optimization, simulation and machine learning

• techniques

• Prototype and pilot new solutions and be a part of the aim

• of ‘productifying’ those valuable solutions that can have impact at a

• global scale

• Guides and coaches other chapter colleagues to help solve

• data/technical problems at an operational level, and in

• methodologies to help improve development processes

• Identifies and interprets trends and patterns in complex data sets to

• enable the business to take data-driven decisions

Job Description

Role:- Software engineer - front end

About the company:-We are a social learning platform that allows us to learn the way we learn best. If our children are going to learn online we will have to make it social. That’s how learning happens best. We think we’re amongst the first few companies in the world trying to push the boundaries of edtech to a new era of highly social & community driven learning.

 Responsibilities:-

You will be responsible for taking end-to-end ownership of the development of beautiful, fast, and responsive mobile and web applications. You will have attention to detail. You will care about the quality of code, design patterns and testability. You will be working closely with designers, product managers and engineers to build products that will delight our educators, students and parents.

HTML, CSS and JavaScript ninja
Patient debugging skills
Using state of the art developer toolkit
React JS / React Native / Vue.js
Curiosity to remain updated with the newest technologies and frameworks