Positive attitude Jobs in Hyderabad

11+ Positive attitude Jobs in Hyderabad | Positive attitude Job openings in Hyderabad

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Jr. US Technical Recruiter

at Antra Inc

7 recruiters

Posted by Jagjeet Kaur

Hyderabad

3 - 4 yrs

₹6L - ₹8L / yr

Business Process Outsourcing (BPO)

Positive attitude

Communication Skills

Title: Junior Technical Recruiter Timings: 6:30 PM to 3:30 AM ( US East coast timings ) Location: Madhapur, Hyderabad Please Note: This is a night shift role and hence please do not apply if you cannot work in the nights. Do you want to work for growing IT Services Company with US based Customers? If below is who you are, we have a job for you. You: ● Have IT Service/Call Center/BPO Experience ● Have great communication and writing skills. ● Are bored of your monotonous job. ● Believe a machine can do your job. ● Love challenges and working with people. ● Want to gain knowledge, have fun and grow. ● Have a can do attitude. ● Have a sense of humor. We: We have lots of ideas, lots of potential and we need someone to help us execute a grand vision. We are a young and vibrant company looking for like-minded people who will help us reach new heights. We thrive in diverse set of experience around us and we welcome high-energy individuals from any functional experience including IT Service or Call Center that want to take their career to the next level. What We Offer: ● Great, positive work environment. ● Challenging and rewarding work ● Opportunity to learn, earn and grow. ● A chance to enhance your career. ● A diverse set of experiences you will always remember and that you can take with you anywhere you go. Our work is exciting and has a positive impact on the people we work with. So, if you choose to accept this mission, your responsibilities would include: ● Identify client needs and recruit technical consultants. ● Contact prospective candidates by phone/email and screen them for fit. ● Negotiate and close deals. ● Collaborate with recruiting and marketing teams ● Understand the business and give ideas on what will make the company better. ● Be awesome! Who We Are: Established in Washington DC Metro area in 2008, Antra has been a leading Information Technology Services provider and has been working diligently to help businesses address critical skill gaps between modern technology adaptation and business enablement to support growth and reach business targets. Our services combine technical knowledge and business savviness to enhance IT capabilities in a cost effective manner. ● 500+employees Company ○ 300 + Technology Consultants in US working at various Clients in IT staff augmentation and IT solution delivery models ○ 100+ Internal administrative and delivery team ● Has offices in Washington, D.C metro region and in Hyderabad, India ● Our employees work on competitive solutions at Fortune 1000 companies ● We are into Professional Services, Digital Marketing, IT Solutions and Antra Labs. We have lots of ideas, lots of potential and we need someone to help us execute a grand vision. We are a young and vibrant company looking for like-minded people who will help us reach new heights. We thrive in diverse set of experience around us and we welcome high-energy individuals from the IT staffing industry. What We Offer: ● Great, positive work environment ● Challenging and rewarding work ● Opportunity to learn, earn and grow ● A chance to enhance your career ● A diverse set of experiences you will always remember and that you can take with you anywhere you go Web: www.antra.com

Lead I - Software Engineering - AI Solutions Analyst

Global Digital Transformation Solutions Provider

Agency job

via Peak Hire Solutions by Dharati Thakkar

Bengaluru (Bangalore), Mumbai, Delhi, Gurugram, Noida, Ghaziabad, Faridabad, Pune, Hyderabad

6 - 8 yrs

₹10L - ₹26L / yr

Large Language Models (LLM)

Prompt engineering

Knowledge base

Large Language Models (LLM) tuning

Artificial Intelligence (AI)

+7 more

MUST-HAVES:

LLM, AI, Prompt Engineering LLM Integration & Prompt Engineering
Context & Knowledge Base Design.
Context & Knowledge Base Design.
Experience running LLM evals

NOTICE PERIOD: Immediate – 30 Days

SKILLS: LLM, AI, PROMPT ENGINEERING

NICE TO HAVES:

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

ROLE PROFICIENCY:

Role Scope / Deliverables:

Scope of Role Serve as the link between business intelligence, data engineering, and AI application teams, ensuring the Large Language Model (LLM) interacts effectively with the modeled dataset.
Define and curate the context and knowledge base that enables GPT to provide accurate, relevant, and compliant business insights.
Collaborate with Data Analysts and System SMEs to identify, structure, and tag data elements that feed the LLM environment.
Design, test, and refine prompt strategies and context frameworks that align GPT outputs with business objectives.
Conduct evaluation and performance testing (evals) to validate LLM responses for accuracy, completeness, and relevance.
Partner with IT and governance stakeholders to ensure secure, ethical, and controlled AI behavior within enterprise boundaries.

KEY DELIVERABLES:

LLM Interaction Design Framework: Documentation of how GPT connects to the modeled dataset, including context injection, prompt templates, and retrieval logic.
Knowledge Base Configuration: Curated and structured domain knowledge to enable precise and useful GPT responses (e.g., commercial definitions, data context, business rules).
Evaluation Scripts & Test Results: Defined eval sets, scoring criteria, and output analysis to measure GPT accuracy and quality over time.
Prompt Library & Usage Guidelines: Standardized prompts and design patterns to ensure consistent business interactions and outcomes.
AI Performance Dashboard / Reporting: Visualizations or reports summarizing GPT response quality, usage trends, and continuous improvement metrics.
Governance & Compliance Documentation: Inputs to data security, bias prevention, and responsible AI practices in collaboration with IT and compliance teams.

KEY SKILLS:

Technical & Analytical Skills:

LLM Integration & Prompt Engineering – Understanding of how GPT models interact with structured and unstructured data to generate business-relevant insights.
Context & Knowledge Base Design – Skilled in curating, structuring, and managing contextual data to optimize GPT accuracy and reliability.
Evaluation & Testing Methods – Experience running LLM evals, defining scoring criteria, and assessing model quality across use cases.
Data Literacy & Modeling Awareness – Familiar with relational and analytical data models to ensure alignment between data structures and AI responses.
Familiarity with Databricks, AWS, and ChatGPT Environments – Capable of working in cloud-based analytics and AI environments for development, testing, and deployment.
Scripting & Query Skills (e.g., SQL, Python) – Ability to extract, transform, and validate data for model training and evaluation workflows.
Business & Collaboration Skills Cross-Functional Collaboration – Works effectively with business, data, and IT teams to align GPT capabilities with business objectives.
Analytical Thinking & Problem Solving – Evaluates LLM outputs critically, identifies improvement opportunities, and translates findings into actionable refinements.
Commercial Context Awareness – Understands how sales and marketing intelligence data should be represented and leveraged by GPT.
Governance & Responsible AI Mindset – Applies enterprise AI standards for data security, privacy, and ethical use.
Communication & Documentation – Clearly articulates AI logic, context structures, and testing results for both technical and non-technical audiences.

MUST-HAVES:

LLM, AI, Prompt Engineering LLM Integration & Prompt Engineering
Context & Knowledge Base Design.
Context & Knowledge Base Design.
Experience running LLM evals

NOTICE PERIOD: Immediate – 30 Days

SKILLS: LLM, AI, PROMPT ENGINEERING

NICE TO HAVES:

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

ROLE PROFICIENCY:

Role Scope / Deliverables:

Scope of Role Serve as the link between business intelligence, data engineering, and AI application teams, ensuring the Large Language Model (LLM) interacts effectively with the modeled dataset.
Define and curate the context and knowledge base that enables GPT to provide accurate, relevant, and compliant business insights.
Collaborate with Data Analysts and System SMEs to identify, structure, and tag data elements that feed the LLM environment.
Design, test, and refine prompt strategies and context frameworks that align GPT outputs with business objectives.
Conduct evaluation and performance testing (evals) to validate LLM responses for accuracy, completeness, and relevance.
Partner with IT and governance stakeholders to ensure secure, ethical, and controlled AI behavior within enterprise boundaries.

KEY DELIVERABLES:

LLM Interaction Design Framework: Documentation of how GPT connects to the modeled dataset, including context injection, prompt templates, and retrieval logic.
Knowledge Base Configuration: Curated and structured domain knowledge to enable precise and useful GPT responses (e.g., commercial definitions, data context, business rules).
Evaluation Scripts & Test Results: Defined eval sets, scoring criteria, and output analysis to measure GPT accuracy and quality over time.
Prompt Library & Usage Guidelines: Standardized prompts and design patterns to ensure consistent business interactions and outcomes.
AI Performance Dashboard / Reporting: Visualizations or reports summarizing GPT response quality, usage trends, and continuous improvement metrics.
Governance & Compliance Documentation: Inputs to data security, bias prevention, and responsible AI practices in collaboration with IT and compliance teams.

KEY SKILLS:

Technical & Analytical Skills:

LLM Integration & Prompt Engineering – Understanding of how GPT models interact with structured and unstructured data to generate business-relevant insights.
Context & Knowledge Base Design – Skilled in curating, structuring, and managing contextual data to optimize GPT accuracy and reliability.
Evaluation & Testing Methods – Experience running LLM evals, defining scoring criteria, and assessing model quality across use cases.
Data Literacy & Modeling Awareness – Familiar with relational and analytical data models to ensure alignment between data structures and AI responses.
Familiarity with Databricks, AWS, and ChatGPT Environments – Capable of working in cloud-based analytics and AI environments for development, testing, and deployment.
Scripting & Query Skills (e.g., SQL, Python) – Ability to extract, transform, and validate data for model training and evaluation workflows.
Business & Collaboration Skills Cross-Functional Collaboration – Works effectively with business, data, and IT teams to align GPT capabilities with business objectives.
Analytical Thinking & Problem Solving – Evaluates LLM outputs critically, identifies improvement opportunities, and translates findings into actionable refinements.
Commercial Context Awareness – Understands how sales and marketing intelligence data should be represented and leveraged by GPT.
Governance & Responsible AI Mindset – Applies enterprise AI standards for data security, privacy, and ethical use.
Communication & Documentation – Clearly articulates AI logic, context structures, and testing results for both technical and non-technical audiences.

Principal Engineer - MERN Stack

at Immersive Infotech Private Limited

Posted by Sanjana Thakur

Hyderabad

10 - 20 yrs

₹30L - ₹40L / yr

MERN Stack

AngularJS (1.x)

Angular (2+)

React.js

NodeJS (Node.js)

+4 more

Job Description: Principal Engineer (Full Stack Architect)

Job Title: Full Stack Architect

Location: Hyderabad, India

Experience: 15Years to 20 years (4+ years in Enterprise Architecture)

Technology Stack: MERN (MongoDB, Express, React, Node.js), Distributed Systems, Cloud (GCP/Azure), Neo4j, Vector Databases, SQL and NoSQL Databases, Knowledge Graphs.

Industry: Enterprise Software, Large-Scale Distributed Systems, Machine Learning

Job Summary

As a Full Stack Architect, you will play a pivotal role in designing and architecting large-scale distributed systems with a strong focus on the MERN stack (MongoDB, Express.js, React, Node.js). You will lead the design and implementation of enterprise-grade software solutions that leverage cloud infrastructure (GCP/Azure), knowledge graphs (Neo4j), vector databases, and machine learning at scale. In this role, you will work closely with cross-functional teams including data scientists, cloud engineers, and front-end developers to deliver high-performance, secure, and scalable applications.

This role requires a deep understanding of distributed systems architecture, graph databases, machine learning systems, and cloud computing, with a strong focus on building solutions that meet business and technical needs. The ideal candidate will have 12+ years of experience with a proven track record of architecting full-stack systems and leading engineering teams in a fast-paced, innovative environment.

Roles and Responsibilities

Full Stack Architecture: Design, develop, and maintain highly scalable, distributed, and fault-tolerant enterprise applications using the MERN stack (MongoDB, Express.js,

React, Node.js).

Distributed Systems: Architect and design large-scale distributed systems that handle high- volume, low-latency data processing.

Cloud Engineering: Implement and maintain cloud infrastructure solutions on GCP or AWS,ensuring high availability, scalability, and performance.

Knowledge Graphs and Databases: Design and optimize complex data models using Neo4j, vector databases, and other NoSQL solutions to manage interconnected data efficiently.

Enterprise Solutions: Architect and deliver cloud-native enterprise software solutions that meet enterprise-grade security, compliance, and performance requirements.

Data Structure & Algorithms (DSA): Lead by example in writing efficient, high-performance code and optimize software with a strong focus on algorithms, data structures, and system design principles.

Collaboration: Work with engineering, data science, and product teams to translate business requirements into scalable technical solutions.

Mentorship: Mentor junior engineers and foster a collaborative team environment.

Performance Optimization: Ensure system performance, scalability, and reliability throughcode reviews, optimizations, and best engineering practices.

Documentation & Best Practices: Maintain comprehensive architecture documentation and promote engineering best practices across teams.

Mandatory Requirements

Experience: 12+ years of full-stack development experience, with significant expertise

in building and architecting applications using the MERN stack (MongoDB, Express.js,

React, Node.js).

 Distributed Systems: Proven track record of architecting and implementing large-scale

distributed systems with a focus on reliability, scalability, and performance.

 Cloud Expertise: Extensive hands-on experience with cloud infrastructure (GCP or AWS),

with a deep understanding of cloud services such as compute, storage, networking, and

security.

 Database Systems: Expertise in NoSQL databases like MongoDB and graph databases like

Neo4j. Experience with vector databases for high-dimensional data processing.

 Knowledge Graphs: Hands-on experience in designing and working with knowledge graphs

for solving complex data relationships.

 Data Structures & Algorithms: Strong knowledge of DSA with practical experience in

solving complex technical challenges.

 Microservices Architecture: Experience in designing and developing microservices-based

architectures and ensuring high availability.

 DevOps ; Automation: Knowledge of DevOps practices (CI/CD), containerization (Docker), and orchestration (Kubernetes).

 Agile Methodologies: Experience with Agile development methodologies, including SCRUM, TDD, and iterative development.

Nice-to-Have Requirements

 Front-End Expertise: Advanced experience with React.js, with knowledge of modern front- end technologies (Next.js, Redux, TypeScript).

 Cloud Certifications: Google Cloud Professional Architect or Azure Certified Solutions Architect certifications.

 Data Engineering: Hands-on experience with data pipelines, ETL processes, and big data technologies (e.g., Apache Spark, Kafka).

 AI/ML Ops: Experience in deploying machine learning models using MLOps frameworks and automating ML pipelines.

 Graph Analytics: Experience in graph algorithms and analytics, with the ability to model and query complex relationships in a graph database.

 System Design: Experience in conducting system design reviews, providing insights into performance bottlenecks, scalability, and trade-offs.

 Security & Compliance: Knowledge of enterprise-level security protocols and data privacy compliance frameworks (e.g., SOC2, GDPR).

Leadership: Proven experience in leading cross-functional teams, setting technical roadmaps, and ensuring alignment between business and technical goals.