Key Account Manager - Ecommerce

About the role

We’re hiring an IT Systems Administrator for an NBFC to secure endpoints, SaaS, and networks across ~50 branches, ~250+ field staff, and ~50+ office users.

This is primarily an IT Admin + Security role, with secondary exposure to AWS cloud ops + light DevOps + basic DB access management.

If you’re an IT Admin aiming to break into AWS Cloud Ops + DevOps, this role is a strong next step — you’ll own core IT/security and get hands-on exposure to cloud operations and deployments.

Key responsibilities (Primary: IT Admin + Security)

• Manage endpoint security for laptops and mobiles (policies, patching, encryption, antivirus/EDR); drive MDM implementation now/future (e.g., Intune/Jamf).
• Administer Google Workspace (Gmail/Drive/Calendar): users, groups, permissions, SSO, MFA, sharing controls.
• Own joiner–mover–leaver lifecycle: provisioning/deprovisioning, access controls, periodic access reviews.
• Secure branch connectivity: VPN, internal Wi-Fi, internet usage controls; coordinate troubleshooting and standardization across branches.
• Manage HO security stack: firewall operations, rule changes with change control, monitoring/log review (basic but consistent).
• Secure SaaS tools (CRM/HRMS/comms like Slack/Zoom): role-based access, MFA enforcement, offboarding, integration/OAuth controls.
• Maintain IT asset inventory: procurement coordination, issuance/return, audits, warranty/AMC, license renewals; remote lock/wipe for lost devices.
• Handle security incidents: phishing, account compromise, device loss/theft — contain, investigate, recover, and prevent recurrence.
• Run backups and basic DR testing; maintain SOPs/documentation and train staff on cyber hygiene.
• Provide hands-on user support: laptop builds, software installs, Outlook/Excel issues, VPN/Wi-Fi troubleshooting, escalations and vendor coordination.

Secondary responsibilities (AWS + DevOps + DB ops support)

• Support AWS administration: IAM users/roles/policies, MFA, access key hygiene, basic log review (e.g., CloudTrail).
• Manage AWS access controls: security groups/firewall rules, IP allowlists/whitelisting (admin tools, databases, vendor access).
• Assist engineering with DevOps operations:
• CI/CD support (deployment coordination, rollbacks, environment configuration)
• Secrets/credentials management and rotation (no shared creds)
• DNS + SSL/TLS certificates, basic monitoring/alerting coordination
• Bonus: Docker/Kubernetes and Terraform exposure
• Basic database operations (admin-lite):
• DB user creation, roles/permissions, least-privilege access
• IP allowlisting/whitelisting for DB access via VPN/approved sources
• Backup/restore verification coordination and basic monitoring signals (connections/storage)

Requirements

• 3+ years in IT security / systems administration (BFSI or branch-heavy org preferred).
• Hands-on with Google Workspace or Microsoft 365 administration.
• Must have hands-on experience leading or executing an email suite migration (e.g., Google Workspace ↔ Microsoft 365), including mailbox migration, DNS cutover, MX/SPF/DKIM/DMARC reconfiguration, and user transition management.
• Strong endpoint/security fundamentals: encryption, patching, AV/EDR, remote support, device compliance.
• Comfortable with networks: VPN/Wi-Fi/LAN troubleshooting; firewall basics and change discipline.
• Strong operational discipline: asset tracking, vendor management, documentation, ticketing, user communication.
• Practical AWS familiarity (IAM, access controls, logging) and ability to support DevOps workflows.

Nice to have

• Experience implementing MDM at scale (Intune/Jamf/SureMDM).
• Exposure to SOC2 / ISO27001 evidence, controls, and audit workflows.
• Scripting for automation (PowerShell/Bash/Python).
• Familiarity with managed databases and secure access patterns.

Job Requirements:

·     Bachelor’s degree (minimum) in Computer Science or Engineering.

·     Minimum 5 years of experience working as a senior–level Software Engineer

·     Excellent programming and debugging skills in C/C++and Python

·     Experience developing on Windows and Linux systems

·     Experience in automation of manual tasks

Although not required, the following are a plus: 

·     Experience working with Build scripts, Shell scripts, Makefiles

·     Experience with Jenkins and other CI/CD tools

·     Knowledge of RESTful web services and docker

Software Engineer

Company Introduction

Since 1983 Windowmaker has been an innovative software business, that has continued to grow year on year due its continued

success. With ongoing market developments and investment within the company, exciting times are ahead of the team!

The Role

We are looking for a full stack engineer to join our team. We ideally hire engineers who are comfortable across the full stack, but

we know you will have a preference about being on the front-end or back-end. As long as you're happy to work on both sets of

tasks – you should carry on reading!

Our Technology

• Front-end: JavaScript, Angular (or good understanding of React, Vue JS, Knockout JS or similar)

• Back-end: C#, ASP.NET, Web API, MVC, Entity Framework

• Database: SQL Server. Knowledge of non-SQL databases is a plus

• Cloud: Microsoft Azure, AWS

Responsibilities

• Design of the overall architecture of the web application

• Implementation of a robust set of services and APIs to power the web application

• Building reusable code and libraries for future use

• Optimization of the application for maximum speed and scalability

• Implementation of security and data protection

• Translation of UI/UX wireframesto visual elements

• Integration of the front-end and back-end aspects of the web application

Additiontionalresponsibilitiesfor Project Lead

• Active participation in design\build cycle of the software engineering life cycle (prototyping, architecture, detailed design,

development, testing and deployment).

• Providing expertise in technical analysis and solving technical issues during project delivery.

• Code reviews, test case reviews and ensure code developed meets the requirements.

• Collaborate with product management and engineering to define and implement innovative solutions for the product

direction, visuals and experience.

• Requirement gathering and understanding, analyze and convert functional requirements into concrete technical tasks and able

to provide reasonable effort estimates

• Mentor and develop skills of junior software engineers in the team.

Tech Skills and Qualifications

• Contract Length : 1 year

• Software Engineering Degree with 3-5 years of experience.

• Expert knowledge of JavaScript and Node.js, good understanding of Angular and JavaScript testing frameworks (such as Jest,

Mocha etc.)

• Good understanding of Cloud Native architecture, containerisation, Docker, Microsoft Azure/AWS, CI/CD, and DevOps

culture.

• Knowledge of cloud-based SaaS applications/architecture.

• Practical experience in the use of leading engineering practices and principles.

• Practical experience of building robust solutions at large scale.

• Appreciation for functions of Product and Design, experience working in cross-functional teams.

• Understanding differences between multiple delivery platforms (such as mobile vs. desktop), and optimizing output to

match the specific platform.

About SkillSecureX

SkillSecureX is a technology-driven platform focused on providing practical learning experiences and industry-oriented opportunities in Artificial Intelligence, Machine Learning, Data Science, Web Development, and emerging technologies. We help students and freshers gain real-world exposure through hands-on projects, mentorship, and internship programs.

About the Internship

We are hiring motivated and enthusiastic candidates for the role of Artificial Intelligence & Machine Learning Intern. This internship is designed for students, freshers, and aspiring AI professionals who want to gain practical experience in AI technologies, Machine Learning concepts, and real-world project development.

Interns will work on practical assignments, AI-based applications, and industry-relevant projects while learning modern tools and technologies used in the AI and ML domain.

Roles & Responsibilities

• Assist in developing AI and Machine Learning models

• Work on data preprocessing and model training

• Analyze datasets and generate insights

• Support research and development activities related to AI solutions

• Work with Python libraries and AI frameworks

• Participate in project discussions and collaborative tasks

• Test, evaluate, and improve model performance

Required Skills

• Basic understanding of Python programming

• Interest in Artificial Intelligence and Machine Learning

• Familiarity with data analysis or statistics concepts is beneficial

• Knowledge of libraries such as NumPy, Pandas, or Scikit-learn is a plus

• Strong analytical and problem-solving skills

• Willingness to learn and work on practical projects

Eligibility

• Students pursuing graduation or post-graduation

• Freshers interested in AI and Machine Learning

• Candidates looking to gain practical industry exposure

Perks & Benefits

• Internship Completion Certificate

• Hands-on experience on practical AI projects

• Flexible remote working environment

• Mentorship and industry-oriented learning

• Opportunity to strengthen technical and professional skills

The Role

You own AI systems end to end. From the speech-to-text models that turn audio into text, to the diarization that separates and identifies speakers, to the agentic layer that turns conversation into memory and action, to the observability and evaluation that keep all of it honest in production. This is a wide role by design. You will own model selection, serving, and production reliability. If you want to tune one model and ignore the system around it, this is not the role.

What You Will Own

•     Speech-to-text. Evaluate, integrate, and optimize STT models across cloud and self-hosted. Drive accuracy and cost trade-offs with ground-truth metrics.

•     Speaker diarization and identification. Push accuracy on hard, real-world, multi-speaker audio.

•     Agentic AI. Build the memory and retrieval pipeline, LLM orchestration, and the agent workflows that sit on top of captured conversation.

•     Model serving and infrastructure. Stand up and optimize self-hosted serving (vLLM, Triton class). Own latency, throughput, and cost per user.

Observability

An always-on wearable means models run in production every second, on messy real-world audio. You own the visibility into that.

•     Instrument the full audio-to-memory pipeline: STT, diarization, retrieval, and LLM calls.

•     Define and track model-quality SLOs in production: transcription drift, diarization error over time, retrieval relevance, latency, throughput, and cost per user.

•     Build dashboards and alerting so model degradation is caught before users feel it.

•     Trace failures across a distributed, always-on system using metrics, logs, and traces.

•     Close the loop. Production signals feed back into evaluation and model selection.

Evaluation

We do not ship what we cannot measure. You own the systems that prove a model is actually better, not just newer.

•     Build and own ground-truth evaluation harnesses for every model in the stack.

•     Measure with real metrics: WER for transcription, DER for diarization, Recall and F1 for retrieval and speaker identification.

•     Build and maintain labeled benchmark datasets that reflect real, messy, multi-speaker audio.

•     Run regression and A/B evaluations on every model swap, prompt change, or pipeline update. Nothing ships on a vibe.

•     Reject anecdotal proxies, single confidence scores, and cherry-picked examples as evidence of quality.

What We Are Looking For

•     3 to 5 years as an AI/ML engineer with production systems behind you. Engineering and production experience is non-negotiable.

•     Depth across the modern AI stack: LLMs, speech models, vector retrieval, model serving.

•     Strong software engineering. You write code that ships and survives contact with real users.

•     Fluency in Python and the production ML ecosystem.

•     Comfort with cloud infrastructure (GCP a plus) and containerized deployment on Kubernetes.

•     A working command of observability and evaluation. You measure first and trust metrics over intuition.

•     First-principles reasoning and metric discipline.

Nice to Have

•     Research background or publications. A strong signal, not a substitute for production work.

•     Audio and speech ML experience (STT, diarization, voice).

•     Experience self-hosting and optimizing open models.

•     Experience with LLM gateway and agent orchestration patterns.

•     Experience building eval harnesses or production model-monitoring systems.

Requirements

Agentic work is must. Audio is good to have

. Self hosting models is a must

 Experience with LLM gateway and agent orchestration is a must have

Director - Data engineering

What are we looking for

real solver?

Solver? Absolutely. But not the usual kind. We're searching for the architects of the audacious & the pioneers of the possible. If you're the type to dismantle assumptions, re-engineer ‘best practices,’ and build solutions that make the future possible NOW, then you're speaking our language.

Your Responsibilities

what you will wake up to solve.

1. Delivery & Tactical Rigor

• Methodology Implementation: Implement and manage a unified, 'DataOps-First' methodology for data engineering delivery (ETL/ELT pipelines, Data Modeling, MLOps, Data Governance) within assigned business units. This ensures predictable outcomes and trusted data integrity by reducing architecture variability at the project level.
• Operational Stewardship: Drive initiatives to optimize team utilization and enhance operational efficiency within the practice. You manage the commercial success of your squads, ensuring data delivery models (from migration to modern data stack implementation) are executed profitably, scalably, and cost-effectively.
• Execution & Technical Resolution
• Technical Escalation: Serve as the primary escalation point for delivery issues, personally leading the resolution of complex data integration bottlenecks and pipeline failures to protect client timelines and data reliability standards.
• Quality Enforcement
• Quality Oversight: Execute and monitor technical data quality standards, ensuring engineering teams adhere to strict policies regarding data lineage, automated quality checks (observability), security/privacy compliance (GDPR/CCPA/PII), and active catalog management.

2. Strategic Growth & Practice Scaling

• Talent & Scaling Execution: Execute the strategy for data engineering talent acquisition and development within your business units. Implement objective metrics to assess and grow the 'Data-Native' DNA of your teams, ensuring squads are consistently equipped to handle petabyte-scale environments and high-impact delivery.
• Offerings Alignment: Drive the adoption of standardized regional offerings (e.g., Modern Data Platform, Data Mesh, Lakehouse Implementation). Ensure your teams leverage the profitable frameworks defined by the practice to accelerate time-to-insight and eliminate architectural fragmentation in client environments.
• Innovation & IP Development: Lead the practical integration of Vector Databases and LLM-ready architectures into project delivery. Champion the hands-on development of IP and reusable accelerators (e.g., automated ingestion engines) that improve delivery speed and enhance data availability across your portfolio.

3. Leadership & Unit Management

• Unit Leadership: Directly lead, mentor, and manage the Engineering Managers and Lead Architects within your business unit. Hold your teams accountable for project-level operational consistency, technical talent development, and strict adherence to the practice's data governance standards.
• Stakeholder Communication: Clearly articulate the business unit’s operational performance, technical quality metrics, and delivery progress to the C-suite Stakeholders and regional client leadership, bridging the gap between technical execution and business value.
• Ecosystem Alignment: Maintain strong technical relationships with key partner contacts (Snowflake, Databricks, AWS/GCP). Align team delivery capabilities with current product roadmaps and ensure squad-level participation in training, certifications, and partner-led enablement opportunities.

Welcome to Searce

The ‘process-first’, AI-native modern tech consultancy that's rewriting the rules.

We don’t do traditional.

As an engineering-led consultancy, we are dedicated to relentlessly improving the real business outcomes. Our solvers co-innovate with clients to futurify operations and make processes smarter, faster & better.

Functional Skills

1. Delivery Management & Operational Excellence

• Methodology Execution: Expert capability in implementing and enforcing a unified delivery methodology (DataOps, Agile, Mesh Principles) within specific business units. Proven track record of auditing squad-level adherence to ensure consistency across the project lifecycle.
• Operational Performance: High proficiency in managing day-to-day operational metrics, including squad utilization, resource forecasting, and productivity tracking. Skilled at optimizing team performance to meet profitability and efficiency targets.
• SOW & Risk Mitigation: Proven experience in operationalizing Statement of Work (SOW) requirements and identifying technical delivery risks early. Expert at mitigating scope creep and data-specific bottlenecks (e.g., latency, ingestion gaps) before they impact client outcomes.
• Technical Escalation Leadership: Demonstrated ability to lead "war room" efforts to resolve complex pipeline failures or data integrity issues. Skilled at providing clear, rapid remediation plans and communicating technical status directly to regional stakeholders.

2. Architectural Implementation & Technical Oversight

• Modern Stack Proficiency: Deep, hands-on expertise in implementing Cloud-Native architectures (Lakehouse, Data Mesh, MPP) on Snowflake, Databricks, or hyperscalers. Ability to conduct deep-dive architectural reviews and course-correct design decisions at the squad level to ensure scalability.
• Operationalizing Governance: Proven experience in embedding data quality and observability (completeness, freshness, accuracy) directly into the CI/CD pipeline. Responsible for technical enforcement of regulatory compliance (GDPR/PII) and maintaining the integrity of data catalogs across active projects.
• Applied Domain Expertise: Practical experience leading the delivery of high-growth solutions, specifically Generative AI infrastructure (RAG, Vector DBs), Real-Time Streaming, and large-scale platform migrations with a focus on zero-downtime execution.
• DataOps & Engineering Standards: Expert-level mastery of DataOps, including the setup and management of orchestration frameworks (Airflow, Dagster) and Infrastructure as Code (IaC). You ensure that automation is a baseline requirement, not an afterthought, for all delivery teams.

3. Unit Management & Commercial Execution

• Unit & Team Management: Proven success in leading and mentoring Engineering Managers and Lead Architects. Responsible for the operational metrics, technical output, and career development of the business unit's talent pool.
• Offerings Implementation & Scoping: Expertise in translating service offerings (e.g., Data Maturity Assessments, Lakehouse Builds) into accurate project scopes, technical estimates, and resource plans to ensure delivery is both profitable and competitive.
• Talent Growth & Mentorship: Functional ability to implement growth frameworks for data engineering roles. Focus on hands-on coaching and scaling high-performance technical talent to meet the demands of complex, petabyte-scale environments.
• Partner Enablement: Functional competence in managing regional technical relationships with major partners (Snowflake, Databricks, GCP/AWS). Drives squad-level certifications, joint technical enablement, and alignment with partner product roadmaps.

Tech Superpowers

• Modern Data Architect – Reimagines business with the Modern Data Stack (MDS) to deliver data mesh implementations, insights, & real value to clients.
• End-to-End Ecosystem Thinker – Builds modular, reusable data products across ingestion, transformation (ETL/ELT), governance, and consumption layers.
• Distributed Compute Savant – Crafts resilient, high-throughput architectures that survive petabyte-scale volume and data skew without breaking the bank.
• Governance & Integrity Guardian – Embeds data quality, complete lineage, and privacy-by-design (GDPR/PII) into every table, view, and pipeline.
• AI-Ready Orchestrator – Engineers pipelines that bridge structured data with Unstructured/Vector stores, powering RAG models and Generative AI workflows.
• Product-Minded Strategist – Balances architectural purity with time-to-insight; treats every dataset as a measurable "Data Product" with clear ROI.
• Pragmatic Stack Curator – Chooses the simplest tools that compound reliability; fluent in SQL, Python, Spark, dbt, and Cloud Warehouses.
• Builder @ Heart – Writes, reviews, and optimizes queries daily; proves architectures with cost-performance benchmarks, not slideware. Business-first, data-second, outcome focused technology leader.

Experience & Relevance

• Executive Experience: Minimum 10+ years of progressive experience in data engineering and analytics, with at least 3 years in a Senior Manager or Director -level role managing multiple technical teams and owning significant operational and efficiency metrics for a large data service line.
• Delivery Standardization: Demonstrated success in defining and implementing globally consistent, repeatable delivery methodologies (DataOps/Agile Data Warehousing) across diverse teams.
• Architectural Depth: Must retain deep, current expertise in Modern Data Stack architectures (Lakehouse, MPP, Mesh) and maintain the ability to personally validate high-level architectural and data pipeline design decisions.
• Operational Leadership: Proven expertise in managing and scaling large professional services organizations, demonstrated ability to optimize utilization, resource allocation, and operational expense.
• Domain Expertise: Strong background in Enterprise Data Platforms, Applied AI/ML, Generative AI integration, or large-scale Cloud Data Migration.
• Communication: Exceptional executive-level presentation and negotiation skills, particularly in communicating complex operational, data quality, and governance metrics to C-level stakeholders.

Join the ‘real solvers’

ready to futurify?

If you are excited by the possibilities of what an AI-native engineering-led, modern tech consultancy can do to futurify businesses, apply here and experience the ‘Art of the possible’. Don’t Just Send a Resume. Send a Statement.

Job Description:

• 5+ years of development experience
• Expertise in IBM MDM version 11.x (Advanced Edition) product, hands-on multiple implementation experience.
• Hands on experience with IBM MDM Customization using features which includes Extension, Addition, Business proxies, SDP, Match-Merge Rules, Event Manager, Notification
• Exposure to MDM Information Domains (Party, Agreement, Location)
• Expert Java, JEE development background with RSA/ RAD, Websphere, MDM Workbench, SOAP Web Services, XML, XSD, WSDL
• Intermediate knowledge of SQL, Joins, Triggers(DB2/Oracle)
• Working knowledge of concepts like Service Oriented Architecture (SOA) and how to use these with different types of integration technologies

Primary Skills

• Expertise in IBM MDM version 11.x
• Hands-on multiple implementation experience.
• Customization using features
• Expert Java, JEE development background
• Intermediate knowledge of SQL

Secondary Skills

• Working knowledge of concepts like Service Oriented Architecture (SOA) and how to use these with different types of integration technologies
• Ability to work both independently and as part of a team

Role Type - Remote | Part-time / Contract

Please fill this google form - https://forms.gle/Bp39VdWikH1jHpKR6

Zapify Pro is an Instagram automation platform offering comment-to-DM automation and AI-powered replies. We help creators and businesses scale engagement and conversions by eliminating manual comment and DM workflows.

About the Role

We’re looking for an SEO Specialist to own and scale organic growth for Zapify Pro. This role is ideal for someone experienced in SaaS SEO, who can drive qualified traffic, product signups, and long-term search visibility.

Key Responsibilities

• Own and execute end-to-end SEO strategy for a SaaS product with clear revenue impact.
• Drive organic → trial → paid conversion growth.
• Perform keyword research focused on high-intent, BOFU, product-led, and content-led keywords.
• Plan, create, and optimize:
• Blog content and topical clusters
• Feature, use-case, comparison, alternatives, and integration pages
• Conversion-focused landing pages (trials, signups)
• Conduct regular SEO audits:
• Technical, on-page, content gaps, and decay analysis
• Improve site architecture, internal linking, crawlability, and indexing.
• Own content refresh, pruning, and cannibalization fixes.
• Collaborate closely with content, product, and engineering teams:
• SEO input for new features and page launches
• Lead white-hat backlink and authority-building initiatives.
• Monitor competitors: Keyword gaps, SERP features, and share of voice
• Track, analyze, and report performance:
• Organic traffic and rankings
• Conversion rates and SEO-assisted revenue
• Insights with clear action plans
• Stay updated with Google algorithm changes and SEO best practices.

Requirements

• 3+ years of hands-on SEO experience with demonstrable SaaS results.
• Strong experience in SaaS or B2B SEO.
• Proven ability to grow organic traffic, trials, and paid signups.
• Deep expertise in:
• On-page, off-page, and technical SEO
• Keyword research, search intent, and competitor analysis
• Solid technical SEO knowledge:
• Core Web Vitals (LCP, CLS, INP)
• Indexing, canonicals, pagination
• Schema (FAQ, Product, Review)
• JavaScript SEO basics (Next.js / React awareness)
• Proficient with:
• Ahrefs or SEMrush
• Google Search Console
• Google Analytics (GA4)
• Basic understanding of HTML/CSS and SEO-friendly development.
• Data-driven mindset with strong ownership and execution ability.
• Clear communication and documentation skills.

Bonus (Nice to Have)

• Experience with product-led SEO or programmatic SEO.
• CRO or landing page optimization experience.
• SaaS comparison / alternatives page strategy experience.
• Familiarity with automation, AI tools, or marketing tech.
• Experience working with headless CMS or modern SaaS stacks.

Job Summary

We are looking for a driven and result-oriented Sales Executive to promote and sell our EdTech products and services. The ideal candidate will be responsible for generating leads, converting prospects into customers, and building long-term relationships with students, parents, schools, or institutions.

Key Responsibilities

• Identify and generate new sales leads through calls, emails, field visits, and digital platforms
• Counsel students/parents or institutional clients on suitable courses and solutions
• Achieve monthly and quarterly sales targets
• Conduct product demonstrations and presentations (online/offline)
• Follow up with leads and maintain a strong sales pipeline
• Maintain accurate records of customer interactions in CRM
• Collaborate with marketing and academic teams to improve conversions
• Handle customer queries and resolve concerns professionally
• Stay updated with EdTech products, course offerings, and industry trends

Required Skills & Qualifications

• Bachelor’s degree in any discipline (MBA in Sales/Marketing is a plus)
• 0–3 years of experience in sales (EdTech experience preferred)
• Excellent communication and interpersonal skills
• Strong negotiation and persuasion abilities
• Target-driven and self-motivated mindset
• Comfortable with calling, follow-ups, and CRM tools
• Ability to work in a fast-paced, performance-driven environment

Preferred Skills

• Experience in B2C/B2B EdTech sales
• Knowledge of online learning platforms and digital education
• Experience handling students, parents, or institutional clients

Team Leadership: Recruit, train, and supervise staff, fostering a motivated and efficient team.

Sales & Profitability: Develop strategies to meet sales targets and enhance store profitability. resources.workable.com

Inventory Management: Oversee stock levels, order merchandise, and ensure efficient inventory control. manatal.com

Customer Service Excellence: Address customer inquiries and complaints, ensuring a high standard of service.

Operational Oversight: Ensure compliance with health and safety regulations and maintain store presentation.