Exlcareer - Recruitment Agency

Key Responsibilities · Design, write, and optimize complex SQL queries, stored procedures, views, and triggers in MS SQL Server. · Collaborate with business analysts and application developers to gather data requirements and implement solutions. · Work within the iPROOF LCNC platform to develop, configure, and deploy business processes and user interfaces. · Document solutions, data structures, and workflows effectively. Required Skills · Strong knowledge of MS SQL Server, including T-SQL, indexing, and performance tuning. · Familiarity with stored procedures, functions, and triggers. · Understanding of relational database design and normalization. · Willingness to learn and work on the iPROOF LCNC platform. · Basic understanding of JSON data structures and its use in dynamic systems. · Good communication and documentation skills. Show more Show less

Responsibilities: 1. Architect and develop scalable AI applications focused on indexing, retrieval systems, and distributed data processing. 2. Collaborate closely with framework engineering, data science, and full-stack teams to deliver an integrated developer experience for building next-generation context-aware applications (i.e., Retrieval-Augmented Generation (RAG)). 3. Design, build, and maintain scalable infrastructure for high-performance indexing, search engines, and vector databases (e.g., Pinecone, Weaviate, FAISS). 4. Implement and optimize large-scale ETL pipelines, ensuring efficient data ingestion, transformation, and indexing workflows. 5. Lead the development of end-to-end indexing pipelines, from data ingestion to API delivery, supporting millions of data points. 6. Deploy and manage containerized services (Docker, Kubernetes) on cloud platforms (AWS, Azure, GCP) via infrastructure-as-code (e.g., Terraform, Pulumi). 7. Collaborate on building and enhancing user-facing APIs that provide developers with advanced data retrieval capabilities. 8. Focus on creating high-performance systems that scale effortlessly, ensuring optimal performance in production environments with massive datasets. 9. Stay updated on the latest advancements in LLMs, indexing techniques, and cloud technologies to integrate them into cutting-edge applications. 10. Drive ML and AI best practices across the organization to ensure scalable, maintainable, and secure AI infrastructure. Show more Show less

Job Description: Full time Non IT Recruiter Work Type - Full time, 6days, WFH We are seeking a skilled and proactive Non IT Recruitment Specialist to join our dynamic team and play a pivotal role in managing our Recruitment Process Outsourcing (RPO) business. The ideal candidate will have a strong background in recruitment, a deep understanding of client needs, and the ability to drive successful hiring outcomes for both our clients and our company. Responsibilities: Collaborate with Clients Establish strong working relationships with clients to understand their hiring needs and objectives. Conduct regular meetings with clients to assess ongoing requirements and provide updates on recruitment progress. End-to-End Recruitment: Manage the full recruitment lifecycle, including sourcing, screening, interviewing, and placing candidates. Craft compelling job descriptions that align with client needs and attract top-tier candidates. Utilize diverse sourcing strategies to identify and engage candidates across multiple platforms. Client Management: Act as the main point of contact for clients, addressing inquiries, concerns, and providing timely updates. Gather feedback from clients to ensure candidate profiles match their expectations and adjust strategies accordingly. Provide timely updates and feedback to clients and candidates throughout the recruitment process. Collaborate with our team and clients to continuously improve our recruitment strategies and processes. Candidate Assessment and Selection: Conduct thorough candidate assessments, evaluating skills, qualifications, and cultural fit. Present shortlisted candidates to clients, ensuring alignment with client requirements. Utilize various sourcing methods, including job boards, social media, professional networks, and referrals, to identify potential candidates. Conduct initial candidate screenings, including phone interviews and assessments, to assess candidates' qualifications and fit for the role. Maintain accurate and up-to-date candidate records and job descriptions in our recruitment database. Process Optimization: Continuously improve recruitment processes to enhance efficiency, quality, and time-to-fill metrics. Implement best practices in candidate assessment, interview techniques, and feedback mechanisms. Performance Metrics: Set and achieve recruitment targets and key performance indicators (KPIs). Track and report on recruitment metrics to clients, demonstrating the value delivered. Qualifications Bachelor's degree in Human Resources, Business Administration, or related field (Master's preferred). Proven experience in end-to-end recruitment, preferably in an RPO or agency environment. Strong client management skills with the ability to build and maintain relationships. Excellent communication skills, both written and verbal. Proficiency in using recruitment tools and platforms. Analytical mindset with the ability to extract and present insights from data. Proactive and solution-oriented approach to challenges. Understanding of various industries and job roles. Strong organizational skills and attention to detail. As a Full time Recruiter, you will have the opportunity to work independently while collaborating with our team, providing valuable recruitment solutions to diverse industries and companies.

The ideal candidate will provide top-level assistance for high level executives. They should be well-organized and be comfortable scheduling meetings and responding to emails on the executive's behalf. Lastly, this individual should be able to draft documents and help the executive with any necessary meeting preparations. Responsibilities Executive Support:  Manage the CEO's schedule, including meetings, appointments, and travel arrangements.  Screen calls, emails, and prioritize urgent matters.  Prepare presentations, reports, and other documents as needed.  Handle confidential information with discretion. Business Operations:  Assist with strategic planning and decision-making.  Oversee administrative tasks, such as expense reports and contract management.  Coordinate with various departments to ensure smooth operations.  Liaise with clients, partners, and stakeholders. Financial Management:  Oversee financial planning, budgeting, and analysis to ensure optimal resource allocation and profitability.  Monitor key financial metrics and identify opportunities for improvement. Team Leadership:  Build, lead, and motivate a high-performing team to achieve business objectives.  Provide guidance and support to team members.  Foster a positive and collaborative work environment.

Key Responsibilities Roles: § Identify, map, and pursue high-potential private projects including residential, commercial, and institutional segments § Build strong, trust-based relationships with builders, architects, interior contractors, and influencers § Generate specifications and product approvals for upcoming or under-construction projects § Conduct thorough project-level market research and competitor tracking § Drive business development activities through field visits, referrals, and site engagement § Achieve monthly sales targets and project pipeline metrics § Collaborate with internal stakeholders to ensure pricing, credit, and service commitments are aligned § Provide periodic MIS on territory updates, prospect funnel, and win/loss analysis

The ideal candidate will be responsible for identifying and fostering a relationship with our suppliers and vendors. You will also oversee the implementation of the supply and production strategies. Responsibilities · Responsible for efficient purchasing of RM/PM, inventory supplies, and capital equipment. Receives purchase requisitions and verifies for accuracy and authorization(s). Periodically evaluates vendors/suppliers and advises Management when vendors are not meeting requirements. Evaluates and recommends new/substitute vendors, when necessary. · Prepares and issues purchase orders; determines and negotiates prices, delivery and credit terms; buys according to established company policies and procedures; maintains accurate purchasing records. · Responsible for evaluating, assessing and selecting vendors based on capabilities, performance and consistent quality. Maintains rapport and good working relationships with vendors; keeps accurate vendor records. · Evaluates inventory reorder levels and quantity price breaks to determine most economical purchasing of inventory and supplies in relationship to company’s cost of capital. Prepares monthly reports and reviews forecast of purchasing commitments with Management. · Expedites purchase orders as necessary and ensures delivery of purchased items for uninterrupted manufacturing flow. · Performs other purchasing or inventory control duties as necessary or as requested.

Responsibilities: 1. Architect and develop scalable AI applications focused on indexing, retrieval systems, and distributed data processing. 2. Collaborate closely with framework engineering, data science, and full-stack teams to deliver an integrated developer experience for building next-generation context-aware applications (i.e., Retrieval-Augmented Generation (RAG)). 3. Design, build, and maintain scalable infrastructure for high-performance indexing, search engines, and vector databases (e.g., Pinecone, Weaviate, FAISS). 4. Implement and optimize large-scale ETL pipelines, ensuring efficient data ingestion, transformation, and indexing workflows. 5. Lead the development of end-to-end indexing pipelines, from data ingestion to API delivery, supporting millions of data points. 6. Deploy and manage containerized services (Docker, Kubernetes) on cloud platforms (AWS, Azure, GCP) via infrastructure-as-code (e.g., Terraform, Pulumi). 7. Collaborate on building and enhancing user-facing APIs that provide developers with advanced data retrieval capabilities. 8. Focus on creating high-performance systems that scale effortlessly, ensuring optimal performance in production environments with massive datasets. 9. Stay updated on the latest advancements in LLMs, indexing techniques, and cloud technologies to integrate them into cutting-edge applications. 10. Drive ML and AI best practices across the organization to ensure scalable, maintainable, and secure AI infrastructure. Qualifications: Educational Background: Bachelor's or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field. PhD preferred. Certifications in Cloud Computing (AWS, Azure, GCP) and ML technologies are a plus. Technical Skills: 1. Expertise in Python and related frameworks (Pydantic, FastAPI, Poetry, etc.) for building scalable AI/ML solutions. 2. Proven experience with indexing technologies: Building, managing, and optimizing vector databases (Pinecone, FAISS, Weaviate) and search engines (Elasticsearch, OpenSearch). 3. Machine Learning/AI Development: Hands-on experience with ML frameworks (e.g., PyTorch, TensorFlow) and fine-tuning LLMs for retrieval-based tasks. 4. Cloud Services & Infrastructure: Deep expertise in architecting and deploying scalable, containerized AI/ML services on cloud platforms using Docker, Kubernetes, and infrastructure-as-code tools like Terraform or Pulumi. 5. Data Engineering: Strong understanding of ETL pipelines, distributed data processing (e.g., Apache Spark, Dask), and data orchestration frameworks (e.g., Apache Airflow, Prefect). 6. APIs Development: Skilled in designing and building RESTful APIs with a focus on user-facing services and seamless integration for developers. 7. Full Stack Engineering: Knowledge of front-end/back-end interactions and how AI models interact with user interfaces. 8. DevOps & MLOps: Experience with CI/CD pipelines, version control (Git), model monitoring, and logging in production environments. Experience with LLMOps tools (Langsmith, MLflow) is a plus. 9. Data Storage: Experience with SQL and NoSQL databases, distributed storage systems, and cloud-native data storage solutions (S3, Google Cloud Storage).

Responsibilities: 1.Architect and develop scalable AI applications focused on indexing, retrieval systems, and distributed data processing. 2.Collaborate closely with framework engineering, data science, and full-stack teams to deliver an integrated developer experience for building next-generation context-aware applications (i.e., Retrieval-Augmented Generation (RAG)). 3.Design, build, and maintain scalable infrastructure for high-performance indexing, search engines, and vector databases (e.g., Pinecone, Weaviate, FAISS). 4.Implement and optimize large-scale ETL pipelines, ensuring efficient data ingestion, transformation, and indexing workflows. 5.Lead the development of end-to-end indexing pipelines, from data ingestion to API delivery, supporting millions of data points. 6.Deploy and manage containerized services (Docker, Kubernetes) on cloud platforms (AWS, Azure, GCP) via infrastructure-as-code (e.g., Terraform, Pulumi). 7.Collaborate on building and enhancing user-facing APIs that provide developers with advanced data retrieval capabilities. 8.Focus on creating high-performance systems that scale effortlessly, ensuring optimal performance in production environments with massive datasets. 9.Stay updated on the latest advancements in LLMs, indexing techniques, and cloud technologies to integrate them into cutting-edge applications. 10.Drive ML and AI best practices across the organization to ensure scalable, maintainable, and secure AI infrastructure. Qualifications: Educational Background: Bachelor&aposs or Masters degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field. PhD preferred. Certifications in Cloud Computing (AWS, Azure, GCP) and ML technologies are a plus. Technical Skills: 1. Expertise in Python and related frameworks (Pydantic, FastAPI, Poetry, etc.) for building scalable AI/ML solutions. 2. Proven experience with indexing technologies: Building, managing, and optimizing vector databases (Pinecone, FAISS, Weaviate) and search engines (Elasticsearch, OpenSearch). 3. Machine Learning/AI Development: Hands-on experience with ML frameworks (e.g., PyTorch, TensorFlow) and fine-tuning LLMs for retrieval-based tasks. 4. Cloud Services & Infrastructure: Deep expertise in architecting and deploying scalable, containerized AI/ML services on cloud platforms using Docker, Kubernetes, and infrastructure-as-code tools like Terraform or Pulumi. 5. Data Engineering: Strong understanding of ETL pipelines, distributed data processing (e.g., Apache Spark, Dask), and data orchestration frameworks (e.g., Apache Airflow, Prefect). 6. APIs Development: Skilled in designing and building RESTful APIs with a focus on user-facing services and seamless integration for developers. 7. Full Stack Engineering: Knowledge of front-end/back-end interactions and how AI models interact with user interfaces. 8. DevOps & MLOps: Experience with CI/CD pipelines, version control (Git), model monitoring, and logging in production environments. Experience with LLMOps tools (Langsmith, MLflow) is a plus. 9. Data Storage: Experience with SQL and NoSQL databases, distributed storage systems, and cloud-native data storage solutions (S3, Google Cloud Storage). Show more Show less